Analyzing the results
diff --git a/pkgdown.yml b/pkgdown.yml
index bfc6d9f4..5e8c78c1 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -5,5 +5,5 @@ articles:
demo: demo.html
implement: implement.html
simulation: simulation.html
-last_built: 2024-04-03T14:24Z
+last_built: 2024-05-01T16:12Z
diff --git a/reference/Rplot002.png b/reference/Rplot002.png
index 876052f3..25b4cd57 100644
Binary files a/reference/Rplot002.png and b/reference/Rplot002.png differ
diff --git a/reference/as.list.lcMethod.html b/reference/as.list.lcMethod.html
index befb7da0..662357f0 100644
--- a/reference/as.list.lcMethod.html
+++ b/reference/as.list.lcMethod.html
@@ -136,13 +136,13 @@ Examples
#> {
#> mean(x, ..., na.rm = TRUE)
#> }
-#> <bytecode: 0x5625eaa19d78>
+#> <bytecode: 0x55be2c0a0a30>
#> <environment: namespace:latrend>
#>
#> $standardize
#> function (x, center = TRUE, scale = TRUE)
#> UseMethod("scale")
-#> <bytecode: 0x5625ea942c70>
+#> <bytecode: 0x55be2c0dc500>
#> <environment: namespace:base>
#>
#> $method
@@ -174,7 +174,7 @@ Examples
#>
#> $formula
#> Y ~ Time
-#> <environment: 0x5625e9e39ee0>
+#> <environment: 0x55be2c3b8ca0>
#>
as.list(method, args = c("id", "time"))
@@ -227,11 +227,11 @@ Examples
#>
#> $distance
#> function(){}
-#> <environment: 0x5625f0c215c0>
+#> <environment: 0x55be2dbe9bf8>
#>
#> $centerMethod
#> function(x){mean(x,na.rm=TRUE)}
-#> <bytecode: 0x5625ee384108>
+#> <bytecode: 0x55be2afd27f0>
#> <environment: namespace:longitudinalData>
#>
#> $startingCond
diff --git a/reference/dot-guessResponseVariable.html b/reference/dot-guessResponseVariable.html
new file mode 100644
index 00000000..58a169ff
--- /dev/null
+++ b/reference/dot-guessResponseVariable.html
@@ -0,0 +1,119 @@
+
+Guess the response variable — .guessResponseVariable • latrend
+
+
+
+
+
+
+
+
+
+
+
+
+ Attempts to identify the response variable for the given trajectory data
+
+
+
+
+
+
+
+ Arguments
+ - data
+A trajectories data.frame.
- id
+Id variable(s) to exclude.
- time
+Time variable(s) to exclude.
- cluster
+Cluster variable(s) to exclude.
+
+
+
+
+
+
+
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+
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+
diff --git a/reference/estimationTime.html b/reference/estimationTime.html
index 71a1674f..5732cb44 100644
--- a/reference/estimationTime.html
+++ b/reference/estimationTime.html
@@ -148,11 +148,11 @@ Examples
model <- latrend(method, latrendData)
estimationTime(model)
-#> [1] 0.094
+#> [1] 0.008
estimationTime(model, unit = 'mins')
-#> [1] 0.001566667
+#> [1] 0.0001333333
estimationTime(model, unit = 'days')
-#> [1] 1.087963e-06
+#> [1] 9.259259e-08
+
+
+
+
+
+
+
+
+
+
+
+ Attempts to identify the response variable for the given trajectory data
+
+
+
+
+
+
+
+ Arguments
+- data +
A trajectories
data.frame.
+
+
+- id +
Id variable(s) to exclude.
+
+
+- time +
Time variable(s) to exclude.
+
+
+- cluster +
Cluster variable(s) to exclude.
+
+
Examples
method <- lcMethodLMKM(Y ~ Time, id = "Id", time = "Time")
formula(method) # Y ~ Time
#> Y ~ Time
-#> <environment: 0x5625f1c842b8>
+#> <environment: 0x55be3370f430>
Examples
model <- latrend(method, data = latrendData) formula(model) # Y ~ Time #> Y ~ Time -#> <environment: 0x5625fef5ed30> +#> <environment: 0x55be405db118> diff --git a/reference/index.html b/reference/index.html index f9e5b562..c4dd936d 100644 --- a/reference/index.html +++ b/reference/index.html @@ -594,7 +594,7 @@All functions
- Extract the trajectories
Get the trajectories
diff --git a/reference/lcMatrixMethod-class.html b/reference/lcMatrixMethod-class.html
index a47349ca..eb6849a3 100644
--- a/reference/lcMatrixMethod-class.html
+++ b/reference/lcMatrixMethod-class.html
@@ -83,7 +83,7 @@ Arguments
...
-Not used.
Arguments passed to trajectoryAssignments for generating the Cluster column.
method
diff --git a/reference/lcMethodDtwclust.html b/reference/lcMethodDtwclust.html
index 7b10cb36..64f3ee1c 100644
--- a/reference/lcMethodDtwclust.html
+++ b/reference/lcMethodDtwclust.html
@@ -157,14 +157,11 @@ Examples
#>
#> Precomputing distance matrix...
#>
-#> Iteration 1: Changes / Distsum = 200 / 582.2736
-#> Iteration 2: Changes / Distsum = 42 / 416.7195
-#> Iteration 3: Changes / Distsum = 16 / 364.8345
-#> Iteration 4: Changes / Distsum = 9 / 354.0672
-#> Iteration 5: Changes / Distsum = 4 / 348.6416
-#> Iteration 6: Changes / Distsum = 0 / 348.6416
+#> Iteration 1: Changes / Distsum = 200 / 468.2995
+#> Iteration 2: Changes / Distsum = 15 / 408.2179
+#> Iteration 3: Changes / Distsum = 0 / 408.2179
#>
-#> Elapsed time is 0.105 seconds.
+#> Elapsed time is 0.154 seconds.
#>
diff --git a/reference/lcMethodMixAK_GLMM.html b/reference/lcMethodMixAK_GLMM.html
index 77383327..d991049e 100644
--- a/reference/lcMethodMixAK_GLMM.html
+++ b/reference/lcMethodMixAK_GLMM.html
@@ -167,13 +167,13 @@ Examples
#>
#> Cluster sizes (K=3):
#> A B C
-#> 79 (27.7%) 0 (24.6%) 121 (47.8%)
+#> 2 (15.1%) 77 (40.7%) 121 (44.2%)
#>
#> Number of obs: 2000, strata (Id): 200
#>
#> Scaled residuals:
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
-#> -3.98524 -0.61917 0.04097 0.00000 0.66109 3.39975
+#> -3.94448 -0.66133 0.02804 0.00000 0.62692 3.21439
#>
diff --git a/reference/lcModel-1.png b/reference/lcModel-1.png
index 5edb4e61..0d3ce254 100644
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diff --git a/reference/min.lcModels.html b/reference/min.lcModels.html
index 6d31a191..5f2eb271 100644
--- a/reference/min.lcModels.html
+++ b/reference/min.lcModels.html
@@ -148,7 +148,7 @@ Examples
#>
#> Cluster sizes (K=3):
#> A B C
-#> 50 (25%) 72 (36%) 78 (39%)
+#> 72 (36%) 50 (25%) 78 (39%)
#>
#> Number of obs: 2000, strata (Id): 200
#>
diff --git a/reference/nClusters.html b/reference/nClusters.html
index 21d1634e..10b9f755 100644
--- a/reference/nClusters.html
+++ b/reference/nClusters.html
@@ -134,7 +134,7 @@ Examples
method <- lcMethodRandom("Y", id = "Id", time = "Time", nClusters = 3)
model <- latrend(method, latrendData)
nClusters(model) # 3
-#> Error in (function (classes, fdef, mtable) { methods <- .findInheritedMethods(classes, fdef, mtable) if (length(methods) == 1L) return(methods[[1L]]) else if (length(methods) == 0L) { cnames <- paste0("\"", vapply(classes, as.character, ""), "\"", collapse = ", ") stop(gettextf("unable to find an inherited method for function %s for signature %s", sQuote(fdef@generic), sQuote(cnames)), domain = NA) } else stop("Internal error in finding inherited methods; didn't return a unique method", domain = NA)})(list(structure("lcModelPartition", package = "latrend")), new("standardGeneric", .Data = function (object, ...) standardGeneric("nClusters"), generic = structure("nClusters", package = "clValid"), package = "clValid", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", "nClusters"), domain = NA))(object, ...)), <environment>): unable to find an inherited method for function ‘nClusters’ for signature ‘"lcModelPartition"’
+#> Error: unable to find an inherited method for function ‘nClusters’ for signature ‘object = "lcModelPartition"’
diff --git a/reference/plot-lcModel-method-1.png b/reference/plot-lcModel-method-1.png
index 1e371db4..2ccaa887 100644
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diff --git a/reference/plot-lcModel-method.html b/reference/plot-lcModel-method.html
index d814cfb4..df5fffa3 100644
--- a/reference/plot-lcModel-method.html
+++ b/reference/plot-lcModel-method.html
@@ -1,5 +1,6 @@
-Plot a lcModel — plot-lcModel-method • latrend Plot a lcModel — plot-lcModel-method • latrend
@@ -62,7 +63,8 @@ Plot a lcModel
- Plot a lcModel object. By default, this plots the cluster trajectories of the model, along with the training data.
+ Plot a lcModel object.
+By default, this plots the cluster trajectories of the model, along with the trajectories used for estimation.
diff --git a/reference/plotClusterTrajectories-1.png b/reference/plotClusterTrajectories-1.png
index a5219c01..0904b9c0 100644
Binary files a/reference/plotClusterTrajectories-1.png and b/reference/plotClusterTrajectories-1.png differ
diff --git a/reference/plotClusterTrajectories.html b/reference/plotClusterTrajectories.html
index 75eaa049..9402f29e 100644
--- a/reference/plotClusterTrajectories.html
+++ b/reference/plotClusterTrajectories.html
@@ -92,7 +92,6 @@ Plot cluster trajectories
clusterLabeler = make.clusterPropLabels,
trajectories = FALSE,
facet = !isFALSE(as.logical(trajectories[1])),
- trajAssignments = trajectoryAssignments(object),
...
)
@@ -162,10 +161,6 @@ Arguments
at
A numeric vector of the times at which to compute the cluster trajectories.
trajAssignments
-The cluster assignments for the fitted trajectories. Only used when trajectories = TRUE and facet = TRUE. See trajectoryAssignments.
Value
diff --git a/reference/plotFittedTrajectories-1.png b/reference/plotFittedTrajectories-1.png
index dbc9e4c0..95b9961e 100644
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diff --git a/reference/plotTrajectories-1.png b/reference/plotTrajectories-1.png
index b73eb6cc..291bbf10 100644
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diff --git a/reference/plotTrajectories-2.png b/reference/plotTrajectories-2.png
index fb8e7d23..8876dc26 100644
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diff --git a/reference/plotTrajectories.html b/reference/plotTrajectories.html
index 2f4a1fad..8730a538 100644
--- a/reference/plotTrajectories.html
+++ b/reference/plotTrajectories.html
@@ -72,9 +72,9 @@ Plot the data trajectories
plotTrajectories(
object,
response,
+ cluster,
time = getOption("latrend.time"),
id = getOption("latrend.id"),
- cluster = NULL,
facet = TRUE,
...
)
@@ -104,6 +104,12 @@ Arguments
Response variable character name or a call.
cluster
+Whether to plot trajectories grouped by cluster (determined by the "Cluster" column).
+Alternatively, the name of the cluster column indicating trajectory cluster membership.
+If unspecified, trajectories are grouped if the object contains a "Cluster" column.
time
The time variable name, see timeVariable.
Arguments
The identifier variable name, see idVariable.
cluster
-Cluster variable name. If unspecified, trajectories are not grouped.
-Alternatively, cluster is a vector indicating cluster membership per id.
facet
Whether to facet by cluster.
Examples
time = "Time",
cluster = "Class"
)
-
- # compute cluster membership based on the mean being below 0
- assignments <- aggregate(Y ~ Id, latrendData, mean)$Y < 0
- plotTrajectories(
- latrendData,
- response = "Y",
- id = "Id",
- time = "Time",
- cluster = assignments
- )
}
data(latrendData)
diff --git a/reference/postprob.html b/reference/postprob.html
index 41749593..9fbae613 100644
--- a/reference/postprob.html
+++ b/reference/postprob.html
@@ -158,206 +158,206 @@ Examples
postprob(model)
#> A B
-#> [1,] 0 1
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+#> [154,] 0 1
+#> [155,] 0 1
+#> [156,] 0 1
+#> [157,] 0 1
+#> [158,] 0 1
+#> [159,] 0 1
+#> [160,] 0 1
+#> [161,] 0 1
+#> [162,] 0 1
+#> [163,] 0 1
+#> [164,] 0 1
+#> [165,] 0 1
+#> [166,] 0 1
+#> [167,] 0 1
+#> [168,] 0 1
+#> [169,] 0 1
+#> [170,] 0 1
+#> [171,] 0 1
+#> [172,] 0 1
+#> [173,] 0 1
+#> [174,] 0 1
+#> [175,] 0 1
+#> [176,] 0 1
+#> [177,] 0 1
+#> [178,] 0 1
+#> [179,] 0 1
+#> [180,] 0 1
+#> [181,] 0 1
+#> [182,] 0 1
+#> [183,] 0 1
+#> [184,] 0 1
+#> [185,] 0 1
+#> [186,] 0 1
+#> [187,] 0 1
+#> [188,] 0 1
+#> [189,] 0 1
+#> [190,] 0 1
+#> [191,] 0 1
+#> [192,] 0 1
+#> [193,] 0 1
+#> [194,] 0 1
+#> [195,] 0 1
+#> [196,] 0 1
+#> [197,] 0 1
+#> [198,] 0 1
+#> [199,] 0 1
+#> [200,] 0 1
if (rlang::is_installed("lcmm")) {
gmmMethod = lcMethodLcmmGMM(
diff --git a/reference/qqPlot-1.png b/reference/qqPlot-1.png
index 93f2c7b9..7d6304b0 100644
Binary files a/reference/qqPlot-1.png and b/reference/qqPlot-1.png differ
diff --git a/reference/trajectories.html b/reference/trajectories.html
index 6cb6cfd9..55906d63 100644
--- a/reference/trajectories.html
+++ b/reference/trajectories.html
@@ -1,6 +1,8 @@
-Extract the trajectories — trajectories • latrend Get the trajectories — trajectories • latrend
@@ -57,14 +59,16 @@
- Extract the trajectories
+ Get the trajectories
Source: R/generics.R, R/trajectories.R, R/model.R
trajectories.Rd
Transform or extract the trajectories from the given object to a standardized format.
-The standardized data format is for method estimation by latrend, and for plotting functions.
+Trajectories are ordered by Id and observation time.
+For estimated models; get the trajectories used for estimation, along with the cluster membership.
+This data can be used for plotting or post-hoc analysis.
@@ -73,6 +77,7 @@ Extract the trajectories
id = idVariable(object),
time = timeVariable(object),
response = responseVariable(object),
+ cluster = "Cluster",
...
)
@@ -82,6 +87,7 @@ Extract the trajectories
id = idVariable(object),
time = timeVariable(object),
response = responseVariable(object),
+ cluster = "Cluster",
...
)
@@ -91,6 +97,7 @@ Extract the trajectories
id = idVariable(object),
time = timeVariable(object),
response = responseVariable(object),
+ cluster = "Cluster",
...
)
@@ -103,6 +110,7 @@ Extract the trajectories
id = idVariable(object),
time = timeVariable(object),
response = responseVariable(object),
+ cluster = "Cluster",
...
)
@@ -125,8 +133,12 @@ Arguments
The response variable name, see responseVariable.
cluster
+Experimental feature for data.frame input: a vector of cluster membership per id
...
-Not used.
Arguments passed to trajectoryAssignments for generating the Cluster column.
envir
@@ -137,17 +149,2027 @@ Arguments
Value
-A data.frame with columns matching the id, time, and response name arguments.
+A data.frame with columns matching the id, time, response and cluster name arguments.
Details
- The generic function removes unused factor levels in the Id column, and any trajectories which are only comprised of NAs in the response.
+ The standardized data format is for method estimation by latrend, and for plotting functions.
+The generic function removes unused factor levels in the Id column, and any trajectories which are only comprised of NAs in the response.
See also
+
+ Examples
+ data(latrendData)
+method <- lcMethodLMKM(Y ~ Time, id = "Id", time = "Time")
+model <- latrend(method, latrendData)
+trajectories(model)
+#> Id Time Y Cluster
+#> 1 1 0.0000000 -1.080492e+00 A
+#> 2 1 0.2222222 -6.802415e-01 A
+#> 3 1 0.4444444 -6.514837e-01 A
+#> 4 1 0.6666667 -3.911540e-01 A
+#> 5 1 0.8888889 -1.940788e-01 A
+#> 6 1 1.1111111 -2.991783e-02 A
+#> 7 1 1.3333333 9.158311e-02 A
+#> 8 1 1.5555556 1.797706e-01 A
+#> 9 1 1.7777778 3.951063e-01 A
+#> 10 1 2.0000000 1.832502e-01 A
+#> 11 2 0.0000000 -9.837238e-01 A
+#> 12 2 0.2222222 -5.473079e-01 A
+#> 13 2 0.4444444 -2.072449e-01 A
+#> 14 2 0.6666667 -1.436001e-01 A
+#> 15 2 0.8888889 9.662936e-02 A
+#> 16 2 1.1111111 3.741209e-01 A
+#> 17 2 1.3333333 5.583489e-01 A
+#> 18 2 1.5555556 5.267654e-01 A
+#> 19 2 1.7777778 4.646849e-01 A
+#> 20 2 2.0000000 7.948924e-01 A
+#> 21 3 0.0000000 -1.107182e+00 A
+#> 22 3 0.2222222 -9.905167e-01 A
+#> 23 3 0.4444444 -6.342835e-01 A
+#> 24 3 0.6666667 -5.515270e-01 A
+#> 25 3 0.8888889 -1.059173e-01 A
+#> 26 3 1.1111111 1.715294e-01 A
+#> 27 3 1.3333333 -1.975520e-02 A
+#> 28 3 1.5555556 1.601880e-01 A
+#> 29 3 1.7777778 2.286929e-01 A
+#> 30 3 2.0000000 2.398571e-01 A
+#> 31 4 0.0000000 -7.247443e-01 A
+#> 32 4 0.2222222 -1.614159e-01 A
+#> 33 4 0.4444444 -9.429476e-02 A
+#> 34 4 0.6666667 2.872764e-01 A
+#> 35 4 0.8888889 5.404596e-01 A
+#> 36 4 1.1111111 6.132204e-01 A
+#> 37 4 1.3333333 8.346134e-01 A
+#> 38 4 1.5555556 8.157076e-01 A
+#> 39 4 1.7777778 7.868733e-01 A
+#> 40 4 2.0000000 9.101294e-01 A
+#> 41 5 0.0000000 -9.445309e-01 A
+#> 42 5 0.2222222 -4.356978e-01 A
+#> 43 5 0.4444444 -3.661023e-01 A
+#> 44 5 0.6666667 -6.981846e-02 A
+#> 45 5 0.8888889 3.508655e-02 A
+#> 46 5 1.1111111 -1.560706e-01 A
+#> 47 5 1.3333333 9.878099e-02 A
+#> 48 5 1.5555556 2.441337e-01 A
+#> 49 5 1.7777778 3.218698e-01 A
+#> 50 5 2.0000000 3.605647e-02 A
+#> 51 6 0.0000000 -1.149971e+00 A
+#> 52 6 0.2222222 -9.652510e-01 A
+#> 53 6 0.4444444 -6.782703e-01 A
+#> 54 6 0.6666667 -4.962241e-01 A
+#> 55 6 0.8888889 -2.632388e-01 A
+#> 56 6 1.1111111 7.109115e-02 A
+#> 57 6 1.3333333 2.601961e-01 A
+#> 58 6 1.5555556 1.037659e-01 A
+#> 59 6 1.7777778 2.779068e-01 A
+#> 60 6 2.0000000 4.572028e-01 A
+#> 61 7 0.0000000 -8.990750e-01 A
+#> 62 7 0.2222222 -3.162423e-01 A
+#> 63 7 0.4444444 -1.267186e-01 A
+#> 64 7 0.6666667 5.023628e-02 A
+#> 65 7 0.8888889 1.936485e-01 A
+#> 66 7 1.1111111 3.840635e-01 A
+#> 67 7 1.3333333 4.089981e-01 A
+#> 68 7 1.5555556 6.263455e-01 A
+#> 69 7 1.7777778 7.560140e-01 A
+#> 70 7 2.0000000 7.212783e-01 A
+#> 71 8 0.0000000 -8.598270e-01 A
+#> 72 8 0.2222222 -6.207953e-01 A
+#> 73 8 0.4444444 -1.897843e-01 A
+#> 74 8 0.6666667 1.058528e-01 A
+#> 75 8 0.8888889 3.979398e-01 A
+#> 76 8 1.1111111 2.925497e-01 A
+#> 77 8 1.3333333 5.829132e-01 A
+#> 78 8 1.5555556 6.523827e-01 A
+#> 79 8 1.7777778 7.914801e-01 A
+#> 80 8 2.0000000 6.728391e-01 A
+#> 81 9 0.0000000 -8.629955e-01 A
+#> 82 9 0.2222222 -6.285156e-01 A
+#> 83 9 0.4444444 -2.916511e-01 A
+#> 84 9 0.6666667 -4.170240e-02 A
+#> 85 9 0.8888889 4.244783e-01 A
+#> 86 9 1.1111111 5.894826e-01 A
+#> 87 9 1.3333333 4.440597e-01 A
+#> 88 9 1.5555556 4.327576e-01 A
+#> 89 9 1.7777778 3.767190e-01 A
+#> 90 9 2.0000000 6.228616e-01 A
+#> 91 10 0.0000000 -1.200674e+00 A
+#> 92 10 0.2222222 -5.439025e-01 A
+#> 93 10 0.4444444 -5.811882e-01 A
+#> 94 10 0.6666667 -2.412800e-01 A
+#> 95 10 0.8888889 3.293666e-01 A
+#> 96 10 1.1111111 -1.328653e-03 A
+#> 97 10 1.3333333 2.620363e-01 A
+#> 98 10 1.5555556 2.028012e-01 A
+#> 99 10 1.7777778 3.909610e-01 A
+#> 100 10 2.0000000 2.720679e-01 A
+#> 101 11 0.0000000 -5.387353e-01 A
+#> 102 11 0.2222222 -2.643987e-01 A
+#> 103 11 0.4444444 -8.078835e-02 A
+#> 104 11 0.6666667 2.714066e-01 A
+#> 105 11 0.8888889 5.626728e-01 A
+#> 106 11 1.1111111 7.766386e-01 A
+#> 107 11 1.3333333 5.941937e-01 A
+#> 108 11 1.5555556 7.812206e-01 A
+#> 109 11 1.7777778 9.573348e-01 A
+#> 110 11 2.0000000 7.256745e-01 A
+#> 111 12 0.0000000 -1.135897e+00 A
+#> 112 12 0.2222222 -6.583827e-01 A
+#> 113 12 0.4444444 -3.827679e-01 A
+#> 114 12 0.6666667 -4.205279e-02 A
+#> 115 12 0.8888889 1.125608e-01 A
+#> 116 12 1.1111111 3.363140e-01 A
+#> 117 12 1.3333333 3.916509e-01 A
+#> 118 12 1.5555556 5.525176e-01 A
+#> 119 12 1.7777778 5.202166e-01 A
+#> 120 12 2.0000000 6.780326e-01 A
+#> 121 13 0.0000000 -1.260105e+00 A
+#> 122 13 0.2222222 -8.481724e-01 A
+#> 123 13 0.4444444 -6.960972e-01 A
+#> 124 13 0.6666667 -3.566909e-01 A
+#> 125 13 0.8888889 -1.916500e-01 A
+#> 126 13 1.1111111 -2.042207e-01 A
+#> 127 13 1.3333333 6.141094e-02 A
+#> 128 13 1.5555556 2.659510e-01 A
+#> 129 13 1.7777778 2.486595e-01 A
+#> 130 13 2.0000000 1.879279e-01 A
+#> 131 14 0.0000000 -1.783642e+00 A
+#> 132 14 0.2222222 -1.249131e+00 A
+#> 133 14 0.4444444 -1.099285e+00 A
+#> 134 14 0.6666667 -9.330387e-01 A
+#> 135 14 0.8888889 -5.438213e-01 A
+#> 136 14 1.1111111 -6.446524e-01 A
+#> 137 14 1.3333333 -4.365322e-01 A
+#> 138 14 1.5555556 -2.773758e-01 A
+#> 139 14 1.7777778 -3.235148e-01 A
+#> 140 14 2.0000000 -4.321330e-01 A
+#> 141 15 0.0000000 -7.043625e-01 A
+#> 142 15 0.2222222 -3.024509e-01 A
+#> 143 15 0.4444444 -1.566331e-03 A
+#> 144 15 0.6666667 1.944902e-01 A
+#> 145 15 0.8888889 5.305120e-01 A
+#> 146 15 1.1111111 5.586155e-01 A
+#> 147 15 1.3333333 6.221944e-01 A
+#> 148 15 1.5555556 8.334759e-01 A
+#> 149 15 1.7777778 6.075780e-01 A
+#> 150 15 2.0000000 8.754605e-01 A
+#> 151 16 0.0000000 -9.637840e-01 A
+#> 152 16 0.2222222 -7.055013e-01 A
+#> 153 16 0.4444444 -5.037680e-01 A
+#> 154 16 0.6666667 -1.800992e-01 A
+#> 155 16 0.8888889 2.263311e-01 A
+#> 156 16 1.1111111 1.694383e-01 A
+#> 157 16 1.3333333 1.435539e-01 A
+#> 158 16 1.5555556 5.513790e-01 A
+#> 159 16 1.7777778 4.739464e-01 A
+#> 160 16 2.0000000 4.874058e-01 A
+#> 161 17 0.0000000 -1.126393e+00 A
+#> 162 17 0.2222222 -6.969631e-01 A
+#> 163 17 0.4444444 -3.539397e-01 A
+#> 164 17 0.6666667 -2.516744e-01 A
+#> 165 17 0.8888889 -6.196773e-02 A
+#> 166 17 1.1111111 2.604942e-01 A
+#> 167 17 1.3333333 2.386981e-01 A
+#> 168 17 1.5555556 3.205717e-01 A
+#> 169 17 1.7777778 3.075906e-01 A
+#> 170 17 2.0000000 4.543123e-01 A
+#> 171 18 0.0000000 -8.162685e-01 A
+#> 172 18 0.2222222 -3.322693e-01 A
+#> 173 18 0.4444444 -7.647547e-02 A
+#> 174 18 0.6666667 1.683667e-02 A
+#> 175 18 0.8888889 3.295751e-01 A
+#> 176 18 1.1111111 4.850401e-01 A
+#> 177 18 1.3333333 5.460491e-01 A
+#> 178 18 1.5555556 7.535891e-01 A
+#> 179 18 1.7777778 3.779811e-01 A
+#> 180 18 2.0000000 4.413298e-01 A
+#> 181 19 0.0000000 -8.912856e-01 A
+#> 182 19 0.2222222 -4.161494e-01 A
+#> 183 19 0.4444444 6.755616e-03 A
+#> 184 19 0.6666667 2.577855e-01 A
+#> 185 19 0.8888889 3.410240e-01 A
+#> 186 19 1.1111111 5.427533e-01 A
+#> 187 19 1.3333333 5.635838e-01 A
+#> 188 19 1.5555556 7.086477e-01 A
+#> 189 19 1.7777778 7.435472e-01 A
+#> 190 19 2.0000000 6.344865e-01 A
+#> 191 20 0.0000000 -8.511591e-01 A
+#> 192 20 0.2222222 -5.222303e-01 A
+#> 193 20 0.4444444 -9.578424e-02 A
+#> 194 20 0.6666667 -1.047966e-01 A
+#> 195 20 0.8888889 -1.796624e-02 A
+#> 196 20 1.1111111 4.253539e-01 A
+#> 197 20 1.3333333 3.824626e-01 A
+#> 198 20 1.5555556 4.965144e-01 A
+#> 199 20 1.7777778 6.671359e-01 A
+#> 200 20 2.0000000 4.973909e-01 A
+#> 201 21 0.0000000 -7.584135e-01 A
+#> 202 21 0.2222222 -2.797421e-01 A
+#> 203 21 0.4444444 -1.223377e-01 A
+#> 204 21 0.6666667 9.436062e-02 A
+#> 205 21 0.8888889 2.022779e-01 A
+#> 206 21 1.1111111 2.385694e-01 A
+#> 207 21 1.3333333 2.993715e-01 A
+#> 208 21 1.5555556 4.839809e-01 A
+#> 209 21 1.7777778 7.242704e-01 A
+#> 210 21 2.0000000 5.245418e-01 A
+#> 211 22 0.0000000 -7.489218e-01 A
+#> 212 22 0.2222222 -4.184928e-01 A
+#> 213 22 0.4444444 -2.161782e-01 A
+#> 214 22 0.6666667 -8.294123e-02 A
+#> 215 22 0.8888889 5.195937e-01 A
+#> 216 22 1.1111111 3.652302e-01 A
+#> 217 22 1.3333333 4.938118e-01 A
+#> 218 22 1.5555556 4.210046e-01 A
+#> 219 22 1.7777778 6.124987e-01 A
+#> 220 22 2.0000000 6.101237e-01 A
+#> 221 23 0.0000000 -1.003182e+00 A
+#> 222 23 0.2222222 -8.497474e-01 A
+#> 223 23 0.4444444 -2.255166e-01 A
+#> 224 23 0.6666667 -5.965912e-05 A
+#> 225 23 0.8888889 8.060012e-02 A
+#> 226 23 1.1111111 5.011825e-02 A
+#> 227 23 1.3333333 3.406893e-01 A
+#> 228 23 1.5555556 3.141312e-01 A
+#> 229 23 1.7777778 3.368333e-01 A
+#> 230 23 2.0000000 4.956039e-01 A
+#> 231 24 0.0000000 -1.719594e+00 A
+#> 232 24 0.2222222 -1.338136e+00 A
+#> 233 24 0.4444444 -1.089848e+00 A
+#> 234 24 0.6666667 -7.839737e-01 A
+#> 235 24 0.8888889 -7.519621e-01 A
+#> 236 24 1.1111111 -5.132420e-01 A
+#> 237 24 1.3333333 -2.590546e-01 A
+#> 238 24 1.5555556 -2.113717e-01 A
+#> 239 24 1.7777778 -3.220349e-01 A
+#> 240 24 2.0000000 -1.749806e-01 A
+#> 241 25 0.0000000 -1.057316e+00 A
+#> 242 25 0.2222222 -5.473713e-01 A
+#> 243 25 0.4444444 -1.807962e-01 A
+#> 244 25 0.6666667 -9.628620e-02 A
+#> 245 25 0.8888889 1.481882e-01 A
+#> 246 25 1.1111111 1.352046e-01 A
+#> 247 25 1.3333333 4.825111e-01 A
+#> 248 25 1.5555556 2.763853e-01 A
+#> 249 25 1.7777778 4.532454e-01 A
+#> 250 25 2.0000000 4.447657e-01 A
+#> 251 26 0.0000000 -1.010746e+00 A
+#> 252 26 0.2222222 -7.655726e-01 A
+#> 253 26 0.4444444 -2.061414e-01 A
+#> 254 26 0.6666667 -2.775033e-01 A
+#> 255 26 0.8888889 1.059987e-01 A
+#> 256 26 1.1111111 -3.780193e-02 A
+#> 257 26 1.3333333 3.925013e-01 A
+#> 258 26 1.5555556 5.398044e-01 A
+#> 259 26 1.7777778 4.374378e-01 A
+#> 260 26 2.0000000 6.339589e-01 A
+#> 261 27 0.0000000 -1.013641e+00 A
+#> 262 27 0.2222222 -6.392049e-01 A
+#> 263 27 0.4444444 -5.507768e-01 A
+#> 264 27 0.6666667 -3.326122e-01 A
+#> 265 27 0.8888889 -2.213248e-01 A
+#> 266 27 1.1111111 7.545760e-02 A
+#> 267 27 1.3333333 8.619469e-02 A
+#> 268 27 1.5555556 3.617543e-01 A
+#> 269 27 1.7777778 3.334246e-01 A
+#> 270 27 2.0000000 5.391234e-01 A
+#> 271 28 0.0000000 -1.556996e+00 A
+#> 272 28 0.2222222 -1.027316e+00 A
+#> 273 28 0.4444444 -9.419863e-01 A
+#> 274 28 0.6666667 -8.181834e-01 A
+#> 275 28 0.8888889 -4.380012e-01 A
+#> 276 28 1.1111111 -5.009192e-01 A
+#> 277 28 1.3333333 -3.648896e-01 A
+#> 278 28 1.5555556 -2.739781e-01 A
+#> 279 28 1.7777778 -1.603782e-01 A
+#> 280 28 2.0000000 -3.016691e-01 A
+#> 281 29 0.0000000 -1.035660e+00 A
+#> 282 29 0.2222222 -9.475712e-01 A
+#> 283 29 0.4444444 -5.297449e-01 A
+#> 284 29 0.6666667 -3.003410e-01 A
+#> 285 29 0.8888889 -2.239719e-01 A
+#> 286 29 1.1111111 -2.512660e-03 A
+#> 287 29 1.3333333 9.297215e-02 A
+#> 288 29 1.5555556 3.332638e-01 A
+#> 289 29 1.7777778 4.321577e-01 A
+#> 290 29 2.0000000 1.721947e-01 A
+#> 291 30 0.0000000 -7.815603e-01 A
+#> 292 30 0.2222222 -5.656577e-01 A
+#> 293 30 0.4444444 -4.778344e-01 A
+#> 294 30 0.6666667 -1.192132e-01 A
+#> 295 30 0.8888889 2.004780e-01 A
+#> 296 30 1.1111111 3.273535e-01 A
+#> 297 30 1.3333333 1.875853e-01 A
+#> 298 30 1.5555556 5.693157e-01 A
+#> 299 30 1.7777778 6.167502e-01 A
+#> 300 30 2.0000000 5.212491e-01 A
+#> 301 31 0.0000000 -6.631530e-01 A
+#> 302 31 0.2222222 -9.261232e-02 A
+#> 303 31 0.4444444 -3.564894e-02 A
+#> 304 31 0.6666667 1.955635e-01 A
+#> 305 31 0.8888889 2.687276e-01 A
+#> 306 31 1.1111111 3.912622e-01 A
+#> 307 31 1.3333333 4.784554e-01 A
+#> 308 31 1.5555556 6.541637e-01 A
+#> 309 31 1.7777778 8.585364e-01 A
+#> 310 31 2.0000000 8.844007e-01 A
+#> 311 32 0.0000000 -8.739998e-01 A
+#> 312 32 0.2222222 -6.196796e-01 A
+#> 313 32 0.4444444 -5.311399e-01 A
+#> 314 32 0.6666667 -4.273265e-01 A
+#> 315 32 0.8888889 -1.747301e-01 A
+#> 316 32 1.1111111 -2.597374e-01 A
+#> 317 32 1.3333333 3.407857e-02 A
+#> 318 32 1.5555556 2.758898e-01 A
+#> 319 32 1.7777778 1.279352e-01 A
+#> 320 32 2.0000000 1.898605e-01 A
+#> 321 33 0.0000000 -8.347644e-01 A
+#> 322 33 0.2222222 -6.551258e-01 A
+#> 323 33 0.4444444 -1.359212e-01 A
+#> 324 33 0.6666667 -9.066441e-02 A
+#> 325 33 0.8888889 7.564201e-03 A
+#> 326 33 1.1111111 2.606247e-01 A
+#> 327 33 1.3333333 2.106316e-01 A
+#> 328 33 1.5555556 5.182962e-01 A
+#> 329 33 1.7777778 5.119958e-01 A
+#> 330 33 2.0000000 4.167752e-01 A
+#> 331 34 0.0000000 -1.064984e+00 A
+#> 332 34 0.2222222 -6.025929e-01 A
+#> 333 34 0.4444444 -5.220501e-01 A
+#> 334 34 0.6666667 -2.732845e-01 A
+#> 335 34 0.8888889 6.892312e-02 A
+#> 336 34 1.1111111 1.432615e-01 A
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+#> 1877 188 1.3333333 -2.596088e-01 B
+#> 1878 188 1.5555556 -3.659618e-01 B
+#> 1879 188 1.7777778 -5.640238e-01 B
+#> 1880 188 2.0000000 -8.254948e-01 B
+#> 1881 189 0.0000000 2.216979e-01 B
+#> 1882 189 0.2222222 2.364060e-01 B
+#> 1883 189 0.4444444 1.640381e-01 B
+#> 1884 189 0.6666667 8.724267e-02 B
+#> 1885 189 0.8888889 -6.184765e-02 B
+#> 1886 189 1.1111111 -2.725620e-01 B
+#> 1887 189 1.3333333 -4.121635e-01 B
+#> 1888 189 1.5555556 -6.222327e-01 B
+#> 1889 189 1.7777778 -8.376862e-01 B
+#> 1890 189 2.0000000 -1.296084e+00 B
+#> 1891 190 0.0000000 1.579767e-01 B
+#> 1892 190 0.2222222 6.881586e-02 B
+#> 1893 190 0.4444444 1.138301e-01 B
+#> 1894 190 0.6666667 1.566408e-01 B
+#> 1895 190 0.8888889 -2.125895e-02 B
+#> 1896 190 1.1111111 -1.203461e-01 B
+#> 1897 190 1.3333333 -2.951722e-01 B
+#> 1898 190 1.5555556 -5.952865e-01 B
+#> 1899 190 1.7777778 -8.057966e-01 B
+#> 1900 190 2.0000000 -1.093218e+00 B
+#> 1901 191 0.0000000 2.167051e-01 B
+#> 1902 191 0.2222222 3.078018e-01 B
+#> 1903 191 0.4444444 2.905337e-01 B
+#> 1904 191 0.6666667 2.517826e-01 B
+#> 1905 191 0.8888889 2.825263e-01 B
+#> 1906 191 1.1111111 2.330478e-01 B
+#> 1907 191 1.3333333 4.012726e-02 B
+#> 1908 191 1.5555556 -1.442316e-01 B
+#> 1909 191 1.7777778 -3.668082e-01 B
+#> 1910 191 2.0000000 -5.322080e-01 B
+#> 1911 192 0.0000000 3.452011e-01 B
+#> 1912 192 0.2222222 4.099050e-01 B
+#> 1913 192 0.4444444 3.808182e-01 B
+#> 1914 192 0.6666667 3.338297e-01 B
+#> 1915 192 0.8888889 2.760796e-01 B
+#> 1916 192 1.1111111 1.557230e-01 B
+#> 1917 192 1.3333333 -6.549760e-02 B
+#> 1918 192 1.5555556 -8.545634e-02 B
+#> 1919 192 1.7777778 -4.773788e-01 B
+#> 1920 192 2.0000000 -6.390562e-01 B
+#> 1921 193 0.0000000 1.150290e-01 B
+#> 1922 193 0.2222222 1.921946e-01 B
+#> 1923 193 0.4444444 2.219970e-01 B
+#> 1924 193 0.6666667 1.786091e-01 B
+#> 1925 193 0.8888889 1.765307e-01 B
+#> 1926 193 1.1111111 3.961088e-02 B
+#> 1927 193 1.3333333 -4.755357e-02 B
+#> 1928 193 1.5555556 -1.315012e-01 B
+#> 1929 193 1.7777778 -4.119738e-01 B
+#> 1930 193 2.0000000 -7.894205e-01 B
+#> 1931 194 0.0000000 3.569231e-01 B
+#> 1932 194 0.2222222 3.793874e-01 B
+#> 1933 194 0.4444444 4.758845e-01 B
+#> 1934 194 0.6666667 3.676239e-01 B
+#> 1935 194 0.8888889 2.535408e-01 B
+#> 1936 194 1.1111111 8.793156e-02 B
+#> 1937 194 1.3333333 -1.520331e-03 B
+#> 1938 194 1.5555556 -1.387824e-01 B
+#> 1939 194 1.7777778 -4.769098e-01 B
+#> 1940 194 2.0000000 -7.439063e-01 B
+#> 1941 195 0.0000000 1.784180e-01 B
+#> 1942 195 0.2222222 2.083848e-01 B
+#> 1943 195 0.4444444 1.419173e-01 B
+#> 1944 195 0.6666667 8.636116e-02 B
+#> 1945 195 0.8888889 1.198104e-02 B
+#> 1946 195 1.1111111 -4.378665e-02 B
+#> 1947 195 1.3333333 -2.603427e-01 B
+#> 1948 195 1.5555556 -4.540236e-01 B
+#> 1949 195 1.7777778 -6.285749e-01 B
+#> 1950 195 2.0000000 -9.493716e-01 B
+#> 1951 196 0.0000000 2.060538e-01 B
+#> 1952 196 0.2222222 2.464836e-01 B
+#> 1953 196 0.4444444 1.205809e-01 B
+#> 1954 196 0.6666667 6.736036e-02 B
+#> 1955 196 0.8888889 -2.242651e-02 B
+#> 1956 196 1.1111111 -1.507189e-01 B
+#> 1957 196 1.3333333 -3.808967e-01 B
+#> 1958 196 1.5555556 -5.662458e-01 B
+#> 1959 196 1.7777778 -8.743055e-01 B
+#> 1960 196 2.0000000 -1.121987e+00 B
+#> 1961 197 0.0000000 3.467559e-01 B
+#> 1962 197 0.2222222 4.536987e-01 B
+#> 1963 197 0.4444444 5.665885e-01 B
+#> 1964 197 0.6666667 4.719877e-01 B
+#> 1965 197 0.8888889 4.070098e-01 B
+#> 1966 197 1.1111111 3.843275e-01 B
+#> 1967 197 1.3333333 7.897134e-02 B
+#> 1968 197 1.5555556 6.798930e-02 B
+#> 1969 197 1.7777778 -1.321147e-01 B
+#> 1970 197 2.0000000 -2.700802e-01 B
+#> 1971 198 0.0000000 1.203713e-01 B
+#> 1972 198 0.2222222 1.451069e-01 B
+#> 1973 198 0.4444444 2.967861e-01 B
+#> 1974 198 0.6666667 1.586670e-01 B
+#> 1975 198 0.8888889 5.829574e-02 B
+#> 1976 198 1.1111111 -3.702909e-02 B
+#> 1977 198 1.3333333 -2.457303e-01 B
+#> 1978 198 1.5555556 -4.841471e-01 B
+#> 1979 198 1.7777778 -6.247883e-01 B
+#> 1980 198 2.0000000 -9.381322e-01 B
+#> 1981 199 0.0000000 2.862516e-01 B
+#> 1982 199 0.2222222 2.453220e-01 B
+#> 1983 199 0.4444444 2.517319e-01 B
+#> 1984 199 0.6666667 2.565302e-01 B
+#> 1985 199 0.8888889 8.622183e-02 B
+#> 1986 199 1.1111111 2.066621e-02 B
+#> 1987 199 1.3333333 -1.198231e-01 B
+#> 1988 199 1.5555556 -3.516931e-01 B
+#> 1989 199 1.7777778 -7.221270e-01 B
+#> 1990 199 2.0000000 -9.454804e-01 B
+#> 1991 200 0.0000000 2.123882e-01 B
+#> 1992 200 0.2222222 3.121701e-01 B
+#> 1993 200 0.4444444 3.016063e-01 B
+#> 1994 200 0.6666667 1.930413e-01 B
+#> 1995 200 0.8888889 1.780560e-01 B
+#> 1996 200 1.1111111 1.483383e-01 B
+#> 1997 200 1.3333333 -3.785807e-03 B
+#> 1998 200 1.5555556 -1.409999e-01 B
+#> 1999 200 1.7777778 -5.030799e-01 B
+#> 2000 200 2.0000000 -7.486002e-01 B
+
+
Extract the trajectories
Get the trajectories
Arguments
Not used.
Arguments passed to trajectoryAssignments for generating the Cluster column.
Examples
#> #> Precomputing distance matrix... #> -#> Iteration 1: Changes / Distsum = 200 / 582.2736 -#> Iteration 2: Changes / Distsum = 42 / 416.7195 -#> Iteration 3: Changes / Distsum = 16 / 364.8345 -#> Iteration 4: Changes / Distsum = 9 / 354.0672 -#> Iteration 5: Changes / Distsum = 4 / 348.6416 -#> Iteration 6: Changes / Distsum = 0 / 348.6416 +#> Iteration 1: Changes / Distsum = 200 / 468.2995 +#> Iteration 2: Changes / Distsum = 15 / 408.2179 +#> Iteration 3: Changes / Distsum = 0 / 408.2179 #> -#> Elapsed time is 0.105 seconds. +#> Elapsed time is 0.154 seconds. #> diff --git a/reference/lcMethodMixAK_GLMM.html b/reference/lcMethodMixAK_GLMM.html index 77383327..d991049e 100644 --- a/reference/lcMethodMixAK_GLMM.html +++ b/reference/lcMethodMixAK_GLMM.html @@ -167,13 +167,13 @@Examples
#> #> Cluster sizes (K=3): #> A B C -#> 79 (27.7%) 0 (24.6%) 121 (47.8%) +#> 2 (15.1%) 77 (40.7%) 121 (44.2%) #> #> Number of obs: 2000, strata (Id): 200 #> #> Scaled residuals: #> Min. 1st Qu. Median Mean 3rd Qu. Max. -#> -3.98524 -0.61917 0.04097 0.00000 0.66109 3.39975 +#> -3.94448 -0.66133 0.02804 0.00000 0.62692 3.21439 #> diff --git a/reference/lcModel-1.png b/reference/lcModel-1.png index 5edb4e61..0d3ce254 100644 Binary files a/reference/lcModel-1.png and b/reference/lcModel-1.png differ diff --git a/reference/min.lcModels.html b/reference/min.lcModels.html index 6d31a191..5f2eb271 100644 --- a/reference/min.lcModels.html +++ b/reference/min.lcModels.html @@ -148,7 +148,7 @@Examples
#> #> Cluster sizes (K=3): #> A B C -#> 50 (25%) 72 (36%) 78 (39%) +#> 72 (36%) 50 (25%) 78 (39%) #> #> Number of obs: 2000, strata (Id): 200 #> diff --git a/reference/nClusters.html b/reference/nClusters.html index 21d1634e..10b9f755 100644 --- a/reference/nClusters.html +++ b/reference/nClusters.html @@ -134,7 +134,7 @@Examples
method <- lcMethodRandom("Y", id = "Id", time = "Time", nClusters = 3) model <- latrend(method, latrendData) nClusters(model) # 3 -#> Error in (function (classes, fdef, mtable) { methods <- .findInheritedMethods(classes, fdef, mtable) if (length(methods) == 1L) return(methods[[1L]]) else if (length(methods) == 0L) { cnames <- paste0("\"", vapply(classes, as.character, ""), "\"", collapse = ", ") stop(gettextf("unable to find an inherited method for function %s for signature %s", sQuote(fdef@generic), sQuote(cnames)), domain = NA) } else stop("Internal error in finding inherited methods; didn't return a unique method", domain = NA)})(list(structure("lcModelPartition", package = "latrend")), new("standardGeneric", .Data = function (object, ...) standardGeneric("nClusters"), generic = structure("nClusters", package = "clValid"), package = "clValid", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", "nClusters"), domain = NA))(object, ...)), <environment>): unable to find an inherited method for function ‘nClusters’ for signature ‘"lcModelPartition"’ +#> Error: unable to find an inherited method for function ‘nClusters’ for signature ‘object = "lcModelPartition"’ diff --git a/reference/plot-lcModel-method-1.png b/reference/plot-lcModel-method-1.png index 1e371db4..2ccaa887 100644 Binary files a/reference/plot-lcModel-method-1.png and b/reference/plot-lcModel-method-1.png differ diff --git a/reference/plot-lcModel-method.html b/reference/plot-lcModel-method.html index d814cfb4..df5fffa3 100644 --- a/reference/plot-lcModel-method.html +++ b/reference/plot-lcModel-method.html @@ -1,5 +1,6 @@ -Plot a lcModel
-
Plot a lcModel object. By default, this plots the cluster trajectories of the model, along with the training data.
Plot a lcModel object.
+By default, this plots the cluster trajectories of the model, along with the trajectories used for estimation.
diff --git a/reference/plotClusterTrajectories-1.png b/reference/plotClusterTrajectories-1.png
index a5219c01..0904b9c0 100644
Binary files a/reference/plotClusterTrajectories-1.png and b/reference/plotClusterTrajectories-1.png differ
diff --git a/reference/plotClusterTrajectories.html b/reference/plotClusterTrajectories.html
index 75eaa049..9402f29e 100644
--- a/reference/plotClusterTrajectories.html
+++ b/reference/plotClusterTrajectories.html
@@ -92,7 +92,6 @@
@@ -162,10 +161,6 @@ Plot cluster trajectories
clusterLabeler = make.clusterPropLabels, trajectories = FALSE, facet = !isFALSE(as.logical(trajectories[1])), - trajAssignments = trajectoryAssignments(object), ... )Arguments
A numeric vector of the times at which to compute the cluster trajectories.
The cluster assignments for the fitted trajectories. Only used when trajectories = TRUE and facet = TRUE. See trajectoryAssignments.
Value
diff --git a/reference/plotFittedTrajectories-1.png b/reference/plotFittedTrajectories-1.png index dbc9e4c0..95b9961e 100644 Binary files a/reference/plotFittedTrajectories-1.png and b/reference/plotFittedTrajectories-1.png differ diff --git a/reference/plotTrajectories-1.png b/reference/plotTrajectories-1.png index b73eb6cc..291bbf10 100644 Binary files a/reference/plotTrajectories-1.png and b/reference/plotTrajectories-1.png differ diff --git a/reference/plotTrajectories-2.png b/reference/plotTrajectories-2.png index fb8e7d23..8876dc26 100644 Binary files a/reference/plotTrajectories-2.png and b/reference/plotTrajectories-2.png differ diff --git a/reference/plotTrajectories.html b/reference/plotTrajectories.html index 2f4a1fad..8730a538 100644 --- a/reference/plotTrajectories.html +++ b/reference/plotTrajectories.html @@ -72,9 +72,9 @@Plot the data trajectories
plotTrajectories( object, response, + cluster, time = getOption("latrend.time"), id = getOption("latrend.id"), - cluster = NULL, facet = TRUE, ... ) @@ -104,6 +104,12 @@Arguments
Response variable character name or a call.
Whether to plot trajectories grouped by cluster (determined by the "Cluster" column). +Alternatively, the name of the cluster column indicating trajectory cluster membership. +If unspecified, trajectories are grouped if the object contains a "Cluster" column.
The time variable name, see timeVariable.
Arguments
The identifier variable name, see idVariable.
Cluster variable name. If unspecified, trajectories are not grouped. -Alternatively, cluster is a vector indicating cluster membership per id.
Whether to facet by cluster.
Examples
time = "Time", cluster = "Class" ) - - # compute cluster membership based on the mean being below 0 - assignments <- aggregate(Y ~ Id, latrendData, mean)$Y < 0 - plotTrajectories( - latrendData, - response = "Y", - id = "Id", - time = "Time", - cluster = assignments - ) }
data(latrendData)
diff --git a/reference/postprob.html b/reference/postprob.html
index 41749593..9fbae613 100644
--- a/reference/postprob.html
+++ b/reference/postprob.html
@@ -158,206 +158,206 @@ Examples
postprob(model) #> A B -#> [1,] 0 1 -#> [2,] 0 1 -#> [3,] 0 1 -#> [4,] 0 1 -#> [5,] 0 1 -#> [6,] 0 1 -#> [7,] 0 1 -#> [8,] 0 1 -#> [9,] 0 1 -#> [10,] 0 1 -#> [11,] 0 1 -#> [12,] 0 1 -#> [13,] 0 1 -#> [14,] 0 1 -#> [15,] 0 1 -#> [16,] 0 1 -#> [17,] 0 1 -#> [18,] 0 1 -#> [19,] 0 1 -#> [20,] 0 1 -#> [21,] 0 1 -#> [22,] 0 1 -#> [23,] 0 1 -#> [24,] 0 1 -#> [25,] 0 1 -#> [26,] 0 1 -#> [27,] 0 1 -#> [28,] 0 1 -#> [29,] 0 1 -#> [30,] 0 1 -#> [31,] 0 1 -#> [32,] 0 1 -#> [33,] 0 1 -#> [34,] 0 1 -#> [35,] 0 1 -#> [36,] 0 1 -#> [37,] 0 1 -#> [38,] 0 1 -#> [39,] 0 1 -#> [40,] 0 1 -#> [41,] 0 1 -#> [42,] 0 1 -#> [43,] 0 1 -#> [44,] 0 1 -#> [45,] 0 1 -#> [46,] 0 1 -#> [47,] 0 1 -#> [48,] 0 1 -#> [49,] 0 1 -#> [50,] 0 1 -#> [51,] 0 1 -#> [52,] 0 1 -#> [53,] 0 1 -#> [54,] 0 1 -#> [55,] 0 1 -#> [56,] 0 1 -#> [57,] 0 1 -#> [58,] 0 1 -#> [59,] 0 1 -#> [60,] 0 1 -#> [61,] 0 1 -#> [62,] 0 1 -#> [63,] 0 1 -#> [64,] 0 1 -#> [65,] 0 1 -#> [66,] 0 1 -#> [67,] 0 1 -#> [68,] 0 1 -#> [69,] 0 1 -#> [70,] 0 1 -#> [71,] 0 1 -#> [72,] 0 1 -#> [73,] 0 1 -#> [74,] 0 1 -#> [75,] 0 1 -#> [76,] 0 1 -#> [77,] 0 1 -#> [78,] 0 1 -#> [79,] 0 1 -#> [80,] 0 1 -#> [81,] 1 0 -#> [82,] 1 0 -#> [83,] 1 0 -#> [84,] 1 0 -#> [85,] 1 0 -#> [86,] 1 0 -#> [87,] 1 0 -#> [88,] 1 0 -#> [89,] 1 0 -#> [90,] 1 0 -#> [91,] 1 0 -#> [92,] 1 0 -#> [93,] 1 0 -#> [94,] 1 0 -#> [95,] 1 0 -#> [96,] 1 0 -#> [97,] 1 0 -#> [98,] 1 0 -#> [99,] 1 0 -#> [100,] 1 0 -#> [101,] 1 0 -#> [102,] 1 0 -#> [103,] 1 0 -#> [104,] 1 0 -#> [105,] 1 0 -#> [106,] 1 0 -#> [107,] 1 0 -#> [108,] 1 0 -#> [109,] 1 0 -#> [110,] 1 0 -#> [111,] 1 0 -#> [112,] 1 0 -#> [113,] 1 0 -#> [114,] 1 0 -#> [115,] 1 0 -#> [116,] 1 0 -#> [117,] 1 0 -#> [118,] 1 0 -#> [119,] 1 0 -#> [120,] 1 0 -#> [121,] 1 0 -#> [122,] 1 0 -#> [123,] 1 0 -#> [124,] 1 0 -#> [125,] 1 0 -#> [126,] 1 0 -#> [127,] 1 0 -#> [128,] 1 0 -#> [129,] 1 0 -#> [130,] 1 0 -#> [131,] 1 0 -#> [132,] 1 0 -#> [133,] 1 0 -#> [134,] 1 0 -#> [135,] 1 0 -#> [136,] 1 0 -#> [137,] 1 0 -#> [138,] 1 0 -#> [139,] 1 0 -#> [140,] 1 0 -#> [141,] 1 0 -#> [142,] 1 0 -#> [143,] 1 0 -#> [144,] 1 0 -#> [145,] 1 0 -#> [146,] 1 0 -#> [147,] 1 0 -#> [148,] 1 0 -#> [149,] 1 0 -#> [150,] 1 0 -#> [151,] 1 0 -#> [152,] 1 0 -#> [153,] 1 0 -#> [154,] 1 0 -#> [155,] 1 0 -#> [156,] 1 0 -#> [157,] 1 0 -#> [158,] 1 0 -#> [159,] 1 0 -#> [160,] 1 0 -#> [161,] 1 0 -#> [162,] 1 0 -#> [163,] 1 0 -#> [164,] 1 0 -#> [165,] 1 0 -#> [166,] 1 0 -#> [167,] 1 0 -#> [168,] 1 0 -#> [169,] 1 0 -#> [170,] 1 0 -#> [171,] 1 0 -#> [172,] 1 0 -#> [173,] 1 0 -#> [174,] 1 0 -#> [175,] 1 0 -#> [176,] 1 0 -#> [177,] 1 0 -#> [178,] 1 0 -#> [179,] 1 0 -#> [180,] 1 0 -#> [181,] 1 0 -#> [182,] 1 0 -#> [183,] 1 0 -#> [184,] 1 0 -#> [185,] 1 0 -#> [186,] 1 0 -#> [187,] 1 0 -#> [188,] 1 0 -#> [189,] 1 0 -#> [190,] 1 0 -#> [191,] 1 0 -#> [192,] 1 0 -#> [193,] 1 0 -#> [194,] 1 0 -#> [195,] 1 0 -#> [196,] 1 0 -#> [197,] 1 0 -#> [198,] 1 0 -#> [199,] 1 0 -#> [200,] 1 0 +#> [1,] 1 0 +#> [2,] 1 0 +#> [3,] 1 0 +#> [4,] 1 0 +#> [5,] 1 0 +#> [6,] 1 0 +#> [7,] 1 0 +#> [8,] 1 0 +#> [9,] 1 0 +#> [10,] 1 0 +#> [11,] 1 0 +#> [12,] 1 0 +#> [13,] 1 0 +#> [14,] 1 0 +#> [15,] 1 0 +#> [16,] 1 0 +#> [17,] 1 0 +#> [18,] 1 0 +#> [19,] 1 0 +#> [20,] 1 0 +#> [21,] 1 0 +#> [22,] 1 0 +#> [23,] 1 0 +#> [24,] 1 0 +#> [25,] 1 0 +#> [26,] 1 0 +#> [27,] 1 0 +#> [28,] 1 0 +#> [29,] 1 0 +#> [30,] 1 0 +#> [31,] 1 0 +#> [32,] 1 0 +#> [33,] 1 0 +#> [34,] 1 0 +#> [35,] 1 0 +#> [36,] 1 0 +#> [37,] 1 0 +#> [38,] 1 0 +#> [39,] 1 0 +#> [40,] 1 0 +#> [41,] 1 0 +#> [42,] 1 0 +#> [43,] 1 0 +#> [44,] 1 0 +#> [45,] 1 0 +#> [46,] 1 0 +#> [47,] 1 0 +#> [48,] 1 0 +#> [49,] 1 0 +#> [50,] 1 0 +#> [51,] 1 0 +#> [52,] 1 0 +#> [53,] 1 0 +#> [54,] 1 0 +#> [55,] 1 0 +#> [56,] 1 0 +#> [57,] 1 0 +#> [58,] 1 0 +#> [59,] 1 0 +#> [60,] 1 0 +#> [61,] 1 0 +#> [62,] 1 0 +#> [63,] 1 0 +#> [64,] 1 0 +#> [65,] 1 0 +#> [66,] 1 0 +#> [67,] 1 0 +#> [68,] 1 0 +#> [69,] 1 0 +#> [70,] 1 0 +#> [71,] 1 0 +#> [72,] 1 0 +#> [73,] 1 0 +#> [74,] 1 0 +#> [75,] 1 0 +#> [76,] 1 0 +#> [77,] 1 0 +#> [78,] 1 0 +#> [79,] 1 0 +#> [80,] 1 0 +#> [81,] 0 1 +#> [82,] 0 1 +#> [83,] 0 1 +#> [84,] 0 1 +#> [85,] 0 1 +#> [86,] 0 1 +#> [87,] 0 1 +#> [88,] 0 1 +#> [89,] 0 1 +#> [90,] 0 1 +#> [91,] 0 1 +#> [92,] 0 1 +#> [93,] 0 1 +#> [94,] 0 1 +#> [95,] 0 1 +#> [96,] 0 1 +#> [97,] 0 1 +#> [98,] 0 1 +#> [99,] 0 1 +#> [100,] 0 1 +#> [101,] 0 1 +#> [102,] 0 1 +#> [103,] 0 1 +#> [104,] 0 1 +#> [105,] 0 1 +#> [106,] 0 1 +#> [107,] 0 1 +#> [108,] 0 1 +#> [109,] 0 1 +#> [110,] 0 1 +#> [111,] 0 1 +#> [112,] 0 1 +#> [113,] 0 1 +#> [114,] 0 1 +#> [115,] 0 1 +#> [116,] 0 1 +#> [117,] 0 1 +#> [118,] 0 1 +#> [119,] 0 1 +#> [120,] 0 1 +#> [121,] 0 1 +#> [122,] 0 1 +#> [123,] 0 1 +#> [124,] 0 1 +#> [125,] 0 1 +#> [126,] 0 1 +#> [127,] 0 1 +#> [128,] 0 1 +#> [129,] 0 1 +#> [130,] 0 1 +#> [131,] 0 1 +#> [132,] 0 1 +#> [133,] 0 1 +#> [134,] 0 1 +#> [135,] 0 1 +#> [136,] 0 1 +#> [137,] 0 1 +#> [138,] 0 1 +#> [139,] 0 1 +#> [140,] 0 1 +#> [141,] 0 1 +#> [142,] 0 1 +#> [143,] 0 1 +#> [144,] 0 1 +#> [145,] 0 1 +#> [146,] 0 1 +#> [147,] 0 1 +#> [148,] 0 1 +#> [149,] 0 1 +#> [150,] 0 1 +#> [151,] 0 1 +#> [152,] 0 1 +#> [153,] 0 1 +#> [154,] 0 1 +#> [155,] 0 1 +#> [156,] 0 1 +#> [157,] 0 1 +#> [158,] 0 1 +#> [159,] 0 1 +#> [160,] 0 1 +#> [161,] 0 1 +#> [162,] 0 1 +#> [163,] 0 1 +#> [164,] 0 1 +#> [165,] 0 1 +#> [166,] 0 1 +#> [167,] 0 1 +#> [168,] 0 1 +#> [169,] 0 1 +#> [170,] 0 1 +#> [171,] 0 1 +#> [172,] 0 1 +#> [173,] 0 1 +#> [174,] 0 1 +#> [175,] 0 1 +#> [176,] 0 1 +#> [177,] 0 1 +#> [178,] 0 1 +#> [179,] 0 1 +#> [180,] 0 1 +#> [181,] 0 1 +#> [182,] 0 1 +#> [183,] 0 1 +#> [184,] 0 1 +#> [185,] 0 1 +#> [186,] 0 1 +#> [187,] 0 1 +#> [188,] 0 1 +#> [189,] 0 1 +#> [190,] 0 1 +#> [191,] 0 1 +#> [192,] 0 1 +#> [193,] 0 1 +#> [194,] 0 1 +#> [195,] 0 1 +#> [196,] 0 1 +#> [197,] 0 1 +#> [198,] 0 1 +#> [199,] 0 1 +#> [200,] 0 1 if (rlang::is_installed("lcmm")) { gmmMethod = lcMethodLcmmGMM( diff --git a/reference/qqPlot-1.png b/reference/qqPlot-1.png index 93f2c7b9..7d6304b0 100644 Binary files a/reference/qqPlot-1.png and b/reference/qqPlot-1.png differ diff --git a/reference/trajectories.html b/reference/trajectories.html index 6cb6cfd9..55906d63 100644 --- a/reference/trajectories.html +++ b/reference/trajectories.html @@ -1,6 +1,8 @@ -
-
Extract the trajectories
+Get the trajectories
Source:R/generics.R, R/trajectories.R, R/model.R
trajectories.RdTransform or extract the trajectories from the given object to a standardized format.
-The standardized data format is for method estimation by latrend, and for plotting functions.
+Trajectories are ordered by Id and observation time.
+For estimated models; get the trajectories used for estimation, along with the cluster membership. +This data can be used for plotting or post-hoc analysis.
@@ -73,6 +77,7 @@
Extract the trajectories
id = idVariable(object), time = timeVariable(object), response = responseVariable(object), + cluster = "Cluster", ... ) @@ -82,6 +87,7 @@Extract the trajectories
id = idVariable(object), time = timeVariable(object), response = responseVariable(object), + cluster = "Cluster", ... ) @@ -91,6 +97,7 @@Extract the trajectories
id = idVariable(object), time = timeVariable(object), response = responseVariable(object), + cluster = "Cluster", ... ) @@ -103,6 +110,7 @@Extract the trajectories
id = idVariable(object), time = timeVariable(object), response = responseVariable(object), + cluster = "Cluster", ... )Arguments
The response variable name, see responseVariable.
Experimental feature for data.frame input: a vector of cluster membership per id
Not used.
Arguments passed to trajectoryAssignments for generating the Cluster column.
Arguments
Value
-A data.frame with columns matching the id, time, and response name arguments.
A data.frame with columns matching the id, time, response and cluster name arguments.
Details
-The generic function removes unused factor levels in the Id column, and any trajectories which are only comprised of NAs in the response.
+The standardized data format is for method estimation by latrend, and for plotting functions.
+The generic function removes unused factor levels in the Id column, and any trajectories which are only comprised of NAs in the response.
See also
+
+
Examples
+data(latrendData)
+method <- lcMethodLMKM(Y ~ Time, id = "Id", time = "Time")
+model <- latrend(method, latrendData)
+trajectories(model)
+#> Id Time Y Cluster
+#> 1 1 0.0000000 -1.080492e+00 A
+#> 2 1 0.2222222 -6.802415e-01 A
+#> 3 1 0.4444444 -6.514837e-01 A
+#> 4 1 0.6666667 -3.911540e-01 A
+#> 5 1 0.8888889 -1.940788e-01 A
+#> 6 1 1.1111111 -2.991783e-02 A
+#> 7 1 1.3333333 9.158311e-02 A
+#> 8 1 1.5555556 1.797706e-01 A
+#> 9 1 1.7777778 3.951063e-01 A
+#> 10 1 2.0000000 1.832502e-01 A
+#> 11 2 0.0000000 -9.837238e-01 A
+#> 12 2 0.2222222 -5.473079e-01 A
+#> 13 2 0.4444444 -2.072449e-01 A
+#> 14 2 0.6666667 -1.436001e-01 A
+#> 15 2 0.8888889 9.662936e-02 A
+#> 16 2 1.1111111 3.741209e-01 A
+#> 17 2 1.3333333 5.583489e-01 A
+#> 18 2 1.5555556 5.267654e-01 A
+#> 19 2 1.7777778 4.646849e-01 A
+#> 20 2 2.0000000 7.948924e-01 A
+#> 21 3 0.0000000 -1.107182e+00 A
+#> 22 3 0.2222222 -9.905167e-01 A
+#> 23 3 0.4444444 -6.342835e-01 A
+#> 24 3 0.6666667 -5.515270e-01 A
+#> 25 3 0.8888889 -1.059173e-01 A
+#> 26 3 1.1111111 1.715294e-01 A
+#> 27 3 1.3333333 -1.975520e-02 A
+#> 28 3 1.5555556 1.601880e-01 A
+#> 29 3 1.7777778 2.286929e-01 A
+#> 30 3 2.0000000 2.398571e-01 A
+#> 31 4 0.0000000 -7.247443e-01 A
+#> 32 4 0.2222222 -1.614159e-01 A
+#> 33 4 0.4444444 -9.429476e-02 A
+#> 34 4 0.6666667 2.872764e-01 A
+#> 35 4 0.8888889 5.404596e-01 A
+#> 36 4 1.1111111 6.132204e-01 A
+#> 37 4 1.3333333 8.346134e-01 A
+#> 38 4 1.5555556 8.157076e-01 A
+#> 39 4 1.7777778 7.868733e-01 A
+#> 40 4 2.0000000 9.101294e-01 A
+#> 41 5 0.0000000 -9.445309e-01 A
+#> 42 5 0.2222222 -4.356978e-01 A
+#> 43 5 0.4444444 -3.661023e-01 A
+#> 44 5 0.6666667 -6.981846e-02 A
+#> 45 5 0.8888889 3.508655e-02 A
+#> 46 5 1.1111111 -1.560706e-01 A
+#> 47 5 1.3333333 9.878099e-02 A
+#> 48 5 1.5555556 2.441337e-01 A
+#> 49 5 1.7777778 3.218698e-01 A
+#> 50 5 2.0000000 3.605647e-02 A
+#> 51 6 0.0000000 -1.149971e+00 A
+#> 52 6 0.2222222 -9.652510e-01 A
+#> 53 6 0.4444444 -6.782703e-01 A
+#> 54 6 0.6666667 -4.962241e-01 A
+#> 55 6 0.8888889 -2.632388e-01 A
+#> 56 6 1.1111111 7.109115e-02 A
+#> 57 6 1.3333333 2.601961e-01 A
+#> 58 6 1.5555556 1.037659e-01 A
+#> 59 6 1.7777778 2.779068e-01 A
+#> 60 6 2.0000000 4.572028e-01 A
+#> 61 7 0.0000000 -8.990750e-01 A
+#> 62 7 0.2222222 -3.162423e-01 A
+#> 63 7 0.4444444 -1.267186e-01 A
+#> 64 7 0.6666667 5.023628e-02 A
+#> 65 7 0.8888889 1.936485e-01 A
+#> 66 7 1.1111111 3.840635e-01 A
+#> 67 7 1.3333333 4.089981e-01 A
+#> 68 7 1.5555556 6.263455e-01 A
+#> 69 7 1.7777778 7.560140e-01 A
+#> 70 7 2.0000000 7.212783e-01 A
+#> 71 8 0.0000000 -8.598270e-01 A
+#> 72 8 0.2222222 -6.207953e-01 A
+#> 73 8 0.4444444 -1.897843e-01 A
+#> 74 8 0.6666667 1.058528e-01 A
+#> 75 8 0.8888889 3.979398e-01 A
+#> 76 8 1.1111111 2.925497e-01 A
+#> 77 8 1.3333333 5.829132e-01 A
+#> 78 8 1.5555556 6.523827e-01 A
+#> 79 8 1.7777778 7.914801e-01 A
+#> 80 8 2.0000000 6.728391e-01 A
+#> 81 9 0.0000000 -8.629955e-01 A
+#> 82 9 0.2222222 -6.285156e-01 A
+#> 83 9 0.4444444 -2.916511e-01 A
+#> 84 9 0.6666667 -4.170240e-02 A
+#> 85 9 0.8888889 4.244783e-01 A
+#> 86 9 1.1111111 5.894826e-01 A
+#> 87 9 1.3333333 4.440597e-01 A
+#> 88 9 1.5555556 4.327576e-01 A
+#> 89 9 1.7777778 3.767190e-01 A
+#> 90 9 2.0000000 6.228616e-01 A
+#> 91 10 0.0000000 -1.200674e+00 A
+#> 92 10 0.2222222 -5.439025e-01 A
+#> 93 10 0.4444444 -5.811882e-01 A
+#> 94 10 0.6666667 -2.412800e-01 A
+#> 95 10 0.8888889 3.293666e-01 A
+#> 96 10 1.1111111 -1.328653e-03 A
+#> 97 10 1.3333333 2.620363e-01 A
+#> 98 10 1.5555556 2.028012e-01 A
+#> 99 10 1.7777778 3.909610e-01 A
+#> 100 10 2.0000000 2.720679e-01 A
+#> 101 11 0.0000000 -5.387353e-01 A
+#> 102 11 0.2222222 -2.643987e-01 A
+#> 103 11 0.4444444 -8.078835e-02 A
+#> 104 11 0.6666667 2.714066e-01 A
+#> 105 11 0.8888889 5.626728e-01 A
+#> 106 11 1.1111111 7.766386e-01 A
+#> 107 11 1.3333333 5.941937e-01 A
+#> 108 11 1.5555556 7.812206e-01 A
+#> 109 11 1.7777778 9.573348e-01 A
+#> 110 11 2.0000000 7.256745e-01 A
+#> 111 12 0.0000000 -1.135897e+00 A
+#> 112 12 0.2222222 -6.583827e-01 A
+#> 113 12 0.4444444 -3.827679e-01 A
+#> 114 12 0.6666667 -4.205279e-02 A
+#> 115 12 0.8888889 1.125608e-01 A
+#> 116 12 1.1111111 3.363140e-01 A
+#> 117 12 1.3333333 3.916509e-01 A
+#> 118 12 1.5555556 5.525176e-01 A
+#> 119 12 1.7777778 5.202166e-01 A
+#> 120 12 2.0000000 6.780326e-01 A
+#> 121 13 0.0000000 -1.260105e+00 A
+#> 122 13 0.2222222 -8.481724e-01 A
+#> 123 13 0.4444444 -6.960972e-01 A
+#> 124 13 0.6666667 -3.566909e-01 A
+#> 125 13 0.8888889 -1.916500e-01 A
+#> 126 13 1.1111111 -2.042207e-01 A
+#> 127 13 1.3333333 6.141094e-02 A
+#> 128 13 1.5555556 2.659510e-01 A
+#> 129 13 1.7777778 2.486595e-01 A
+#> 130 13 2.0000000 1.879279e-01 A
+#> 131 14 0.0000000 -1.783642e+00 A
+#> 132 14 0.2222222 -1.249131e+00 A
+#> 133 14 0.4444444 -1.099285e+00 A
+#> 134 14 0.6666667 -9.330387e-01 A
+#> 135 14 0.8888889 -5.438213e-01 A
+#> 136 14 1.1111111 -6.446524e-01 A
+#> 137 14 1.3333333 -4.365322e-01 A
+#> 138 14 1.5555556 -2.773758e-01 A
+#> 139 14 1.7777778 -3.235148e-01 A
+#> 140 14 2.0000000 -4.321330e-01 A
+#> 141 15 0.0000000 -7.043625e-01 A
+#> 142 15 0.2222222 -3.024509e-01 A
+#> 143 15 0.4444444 -1.566331e-03 A
+#> 144 15 0.6666667 1.944902e-01 A
+#> 145 15 0.8888889 5.305120e-01 A
+#> 146 15 1.1111111 5.586155e-01 A
+#> 147 15 1.3333333 6.221944e-01 A
+#> 148 15 1.5555556 8.334759e-01 A
+#> 149 15 1.7777778 6.075780e-01 A
+#> 150 15 2.0000000 8.754605e-01 A
+#> 151 16 0.0000000 -9.637840e-01 A
+#> 152 16 0.2222222 -7.055013e-01 A
+#> 153 16 0.4444444 -5.037680e-01 A
+#> 154 16 0.6666667 -1.800992e-01 A
+#> 155 16 0.8888889 2.263311e-01 A
+#> 156 16 1.1111111 1.694383e-01 A
+#> 157 16 1.3333333 1.435539e-01 A
+#> 158 16 1.5555556 5.513790e-01 A
+#> 159 16 1.7777778 4.739464e-01 A
+#> 160 16 2.0000000 4.874058e-01 A
+#> 161 17 0.0000000 -1.126393e+00 A
+#> 162 17 0.2222222 -6.969631e-01 A
+#> 163 17 0.4444444 -3.539397e-01 A
+#> 164 17 0.6666667 -2.516744e-01 A
+#> 165 17 0.8888889 -6.196773e-02 A
+#> 166 17 1.1111111 2.604942e-01 A
+#> 167 17 1.3333333 2.386981e-01 A
+#> 168 17 1.5555556 3.205717e-01 A
+#> 169 17 1.7777778 3.075906e-01 A
+#> 170 17 2.0000000 4.543123e-01 A
+#> 171 18 0.0000000 -8.162685e-01 A
+#> 172 18 0.2222222 -3.322693e-01 A
+#> 173 18 0.4444444 -7.647547e-02 A
+#> 174 18 0.6666667 1.683667e-02 A
+#> 175 18 0.8888889 3.295751e-01 A
+#> 176 18 1.1111111 4.850401e-01 A
+#> 177 18 1.3333333 5.460491e-01 A
+#> 178 18 1.5555556 7.535891e-01 A
+#> 179 18 1.7777778 3.779811e-01 A
+#> 180 18 2.0000000 4.413298e-01 A
+#> 181 19 0.0000000 -8.912856e-01 A
+#> 182 19 0.2222222 -4.161494e-01 A
+#> 183 19 0.4444444 6.755616e-03 A
+#> 184 19 0.6666667 2.577855e-01 A
+#> 185 19 0.8888889 3.410240e-01 A
+#> 186 19 1.1111111 5.427533e-01 A
+#> 187 19 1.3333333 5.635838e-01 A
+#> 188 19 1.5555556 7.086477e-01 A
+#> 189 19 1.7777778 7.435472e-01 A
+#> 190 19 2.0000000 6.344865e-01 A
+#> 191 20 0.0000000 -8.511591e-01 A
+#> 192 20 0.2222222 -5.222303e-01 A
+#> 193 20 0.4444444 -9.578424e-02 A
+#> 194 20 0.6666667 -1.047966e-01 A
+#> 195 20 0.8888889 -1.796624e-02 A
+#> 196 20 1.1111111 4.253539e-01 A
+#> 197 20 1.3333333 3.824626e-01 A
+#> 198 20 1.5555556 4.965144e-01 A
+#> 199 20 1.7777778 6.671359e-01 A
+#> 200 20 2.0000000 4.973909e-01 A
+#> 201 21 0.0000000 -7.584135e-01 A
+#> 202 21 0.2222222 -2.797421e-01 A
+#> 203 21 0.4444444 -1.223377e-01 A
+#> 204 21 0.6666667 9.436062e-02 A
+#> 205 21 0.8888889 2.022779e-01 A
+#> 206 21 1.1111111 2.385694e-01 A
+#> 207 21 1.3333333 2.993715e-01 A
+#> 208 21 1.5555556 4.839809e-01 A
+#> 209 21 1.7777778 7.242704e-01 A
+#> 210 21 2.0000000 5.245418e-01 A
+#> 211 22 0.0000000 -7.489218e-01 A
+#> 212 22 0.2222222 -4.184928e-01 A
+#> 213 22 0.4444444 -2.161782e-01 A
+#> 214 22 0.6666667 -8.294123e-02 A
+#> 215 22 0.8888889 5.195937e-01 A
+#> 216 22 1.1111111 3.652302e-01 A
+#> 217 22 1.3333333 4.938118e-01 A
+#> 218 22 1.5555556 4.210046e-01 A
+#> 219 22 1.7777778 6.124987e-01 A
+#> 220 22 2.0000000 6.101237e-01 A
+#> 221 23 0.0000000 -1.003182e+00 A
+#> 222 23 0.2222222 -8.497474e-01 A
+#> 223 23 0.4444444 -2.255166e-01 A
+#> 224 23 0.6666667 -5.965912e-05 A
+#> 225 23 0.8888889 8.060012e-02 A
+#> 226 23 1.1111111 5.011825e-02 A
+#> 227 23 1.3333333 3.406893e-01 A
+#> 228 23 1.5555556 3.141312e-01 A
+#> 229 23 1.7777778 3.368333e-01 A
+#> 230 23 2.0000000 4.956039e-01 A
+#> 231 24 0.0000000 -1.719594e+00 A
+#> 232 24 0.2222222 -1.338136e+00 A
+#> 233 24 0.4444444 -1.089848e+00 A
+#> 234 24 0.6666667 -7.839737e-01 A
+#> 235 24 0.8888889 -7.519621e-01 A
+#> 236 24 1.1111111 -5.132420e-01 A
+#> 237 24 1.3333333 -2.590546e-01 A
+#> 238 24 1.5555556 -2.113717e-01 A
+#> 239 24 1.7777778 -3.220349e-01 A
+#> 240 24 2.0000000 -1.749806e-01 A
+#> 241 25 0.0000000 -1.057316e+00 A
+#> 242 25 0.2222222 -5.473713e-01 A
+#> 243 25 0.4444444 -1.807962e-01 A
+#> 244 25 0.6666667 -9.628620e-02 A
+#> 245 25 0.8888889 1.481882e-01 A
+#> 246 25 1.1111111 1.352046e-01 A
+#> 247 25 1.3333333 4.825111e-01 A
+#> 248 25 1.5555556 2.763853e-01 A
+#> 249 25 1.7777778 4.532454e-01 A
+#> 250 25 2.0000000 4.447657e-01 A
+#> 251 26 0.0000000 -1.010746e+00 A
+#> 252 26 0.2222222 -7.655726e-01 A
+#> 253 26 0.4444444 -2.061414e-01 A
+#> 254 26 0.6666667 -2.775033e-01 A
+#> 255 26 0.8888889 1.059987e-01 A
+#> 256 26 1.1111111 -3.780193e-02 A
+#> 257 26 1.3333333 3.925013e-01 A
+#> 258 26 1.5555556 5.398044e-01 A
+#> 259 26 1.7777778 4.374378e-01 A
+#> 260 26 2.0000000 6.339589e-01 A
+#> 261 27 0.0000000 -1.013641e+00 A
+#> 262 27 0.2222222 -6.392049e-01 A
+#> 263 27 0.4444444 -5.507768e-01 A
+#> 264 27 0.6666667 -3.326122e-01 A
+#> 265 27 0.8888889 -2.213248e-01 A
+#> 266 27 1.1111111 7.545760e-02 A
+#> 267 27 1.3333333 8.619469e-02 A
+#> 268 27 1.5555556 3.617543e-01 A
+#> 269 27 1.7777778 3.334246e-01 A
+#> 270 27 2.0000000 5.391234e-01 A
+#> 271 28 0.0000000 -1.556996e+00 A
+#> 272 28 0.2222222 -1.027316e+00 A
+#> 273 28 0.4444444 -9.419863e-01 A
+#> 274 28 0.6666667 -8.181834e-01 A
+#> 275 28 0.8888889 -4.380012e-01 A
+#> 276 28 1.1111111 -5.009192e-01 A
+#> 277 28 1.3333333 -3.648896e-01 A
+#> 278 28 1.5555556 -2.739781e-01 A
+#> 279 28 1.7777778 -1.603782e-01 A
+#> 280 28 2.0000000 -3.016691e-01 A
+#> 281 29 0.0000000 -1.035660e+00 A
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+#> 1827 183 1.3333333 -2.307617e-01 B
+#> 1828 183 1.5555556 -3.912649e-01 B
+#> 1829 183 1.7777778 -7.171692e-01 B
+#> 1830 183 2.0000000 -1.002527e+00 B
+#> 1831 184 0.0000000 1.422954e-01 B
+#> 1832 184 0.2222222 1.156224e-01 B
+#> 1833 184 0.4444444 4.135124e-02 B
+#> 1834 184 0.6666667 1.020364e-01 B
+#> 1835 184 0.8888889 8.517013e-02 B
+#> 1836 184 1.1111111 -1.031983e-01 B
+#> 1837 184 1.3333333 -2.193899e-01 B
+#> 1838 184 1.5555556 -4.775650e-01 B
+#> 1839 184 1.7777778 -7.331339e-01 B
+#> 1840 184 2.0000000 -9.420013e-01 B
+#> 1841 185 0.0000000 2.828538e-01 B
+#> 1842 185 0.2222222 4.056863e-01 B
+#> 1843 185 0.4444444 4.331774e-01 B
+#> 1844 185 0.6666667 3.474479e-01 B
+#> 1845 185 0.8888889 3.159667e-01 B
+#> 1846 185 1.1111111 2.604046e-01 B
+#> 1847 185 1.3333333 1.512809e-01 B
+#> 1848 185 1.5555556 -1.171127e-01 B
+#> 1849 185 1.7777778 -3.365027e-01 B
+#> 1850 185 2.0000000 -5.827436e-01 B
+#> 1851 186 0.0000000 2.946247e-01 B
+#> 1852 186 0.2222222 2.310219e-01 B
+#> 1853 186 0.4444444 2.312479e-01 B
+#> 1854 186 0.6666667 2.065331e-01 B
+#> 1855 186 0.8888889 7.045477e-02 B
+#> 1856 186 1.1111111 -9.437856e-03 B
+#> 1857 186 1.3333333 -1.711472e-01 B
+#> 1858 186 1.5555556 -3.506863e-01 B
+#> 1859 186 1.7777778 -5.616429e-01 B
+#> 1860 186 2.0000000 -7.987087e-01 B
+#> 1861 187 0.0000000 4.370242e-01 B
+#> 1862 187 0.2222222 3.213787e-01 B
+#> 1863 187 0.4444444 4.091530e-01 B
+#> 1864 187 0.6666667 2.837396e-01 B
+#> 1865 187 0.8888889 1.165839e-01 B
+#> 1866 187 1.1111111 1.101641e-02 B
+#> 1867 187 1.3333333 -2.381389e-01 B
+#> 1868 187 1.5555556 -5.214907e-01 B
+#> 1869 187 1.7777778 -8.309639e-01 B
+#> 1870 187 2.0000000 -1.085084e+00 B
+#> 1871 188 0.0000000 6.283395e-02 B
+#> 1872 188 0.2222222 2.091131e-01 B
+#> 1873 188 0.4444444 1.644614e-01 B
+#> 1874 188 0.6666667 8.426455e-02 B
+#> 1875 188 0.8888889 1.213489e-01 B
+#> 1876 188 1.1111111 -1.073654e-02 B
+#> 1877 188 1.3333333 -2.596088e-01 B
+#> 1878 188 1.5555556 -3.659618e-01 B
+#> 1879 188 1.7777778 -5.640238e-01 B
+#> 1880 188 2.0000000 -8.254948e-01 B
+#> 1881 189 0.0000000 2.216979e-01 B
+#> 1882 189 0.2222222 2.364060e-01 B
+#> 1883 189 0.4444444 1.640381e-01 B
+#> 1884 189 0.6666667 8.724267e-02 B
+#> 1885 189 0.8888889 -6.184765e-02 B
+#> 1886 189 1.1111111 -2.725620e-01 B
+#> 1887 189 1.3333333 -4.121635e-01 B
+#> 1888 189 1.5555556 -6.222327e-01 B
+#> 1889 189 1.7777778 -8.376862e-01 B
+#> 1890 189 2.0000000 -1.296084e+00 B
+#> 1891 190 0.0000000 1.579767e-01 B
+#> 1892 190 0.2222222 6.881586e-02 B
+#> 1893 190 0.4444444 1.138301e-01 B
+#> 1894 190 0.6666667 1.566408e-01 B
+#> 1895 190 0.8888889 -2.125895e-02 B
+#> 1896 190 1.1111111 -1.203461e-01 B
+#> 1897 190 1.3333333 -2.951722e-01 B
+#> 1898 190 1.5555556 -5.952865e-01 B
+#> 1899 190 1.7777778 -8.057966e-01 B
+#> 1900 190 2.0000000 -1.093218e+00 B
+#> 1901 191 0.0000000 2.167051e-01 B
+#> 1902 191 0.2222222 3.078018e-01 B
+#> 1903 191 0.4444444 2.905337e-01 B
+#> 1904 191 0.6666667 2.517826e-01 B
+#> 1905 191 0.8888889 2.825263e-01 B
+#> 1906 191 1.1111111 2.330478e-01 B
+#> 1907 191 1.3333333 4.012726e-02 B
+#> 1908 191 1.5555556 -1.442316e-01 B
+#> 1909 191 1.7777778 -3.668082e-01 B
+#> 1910 191 2.0000000 -5.322080e-01 B
+#> 1911 192 0.0000000 3.452011e-01 B
+#> 1912 192 0.2222222 4.099050e-01 B
+#> 1913 192 0.4444444 3.808182e-01 B
+#> 1914 192 0.6666667 3.338297e-01 B
+#> 1915 192 0.8888889 2.760796e-01 B
+#> 1916 192 1.1111111 1.557230e-01 B
+#> 1917 192 1.3333333 -6.549760e-02 B
+#> 1918 192 1.5555556 -8.545634e-02 B
+#> 1919 192 1.7777778 -4.773788e-01 B
+#> 1920 192 2.0000000 -6.390562e-01 B
+#> 1921 193 0.0000000 1.150290e-01 B
+#> 1922 193 0.2222222 1.921946e-01 B
+#> 1923 193 0.4444444 2.219970e-01 B
+#> 1924 193 0.6666667 1.786091e-01 B
+#> 1925 193 0.8888889 1.765307e-01 B
+#> 1926 193 1.1111111 3.961088e-02 B
+#> 1927 193 1.3333333 -4.755357e-02 B
+#> 1928 193 1.5555556 -1.315012e-01 B
+#> 1929 193 1.7777778 -4.119738e-01 B
+#> 1930 193 2.0000000 -7.894205e-01 B
+#> 1931 194 0.0000000 3.569231e-01 B
+#> 1932 194 0.2222222 3.793874e-01 B
+#> 1933 194 0.4444444 4.758845e-01 B
+#> 1934 194 0.6666667 3.676239e-01 B
+#> 1935 194 0.8888889 2.535408e-01 B
+#> 1936 194 1.1111111 8.793156e-02 B
+#> 1937 194 1.3333333 -1.520331e-03 B
+#> 1938 194 1.5555556 -1.387824e-01 B
+#> 1939 194 1.7777778 -4.769098e-01 B
+#> 1940 194 2.0000000 -7.439063e-01 B
+#> 1941 195 0.0000000 1.784180e-01 B
+#> 1942 195 0.2222222 2.083848e-01 B
+#> 1943 195 0.4444444 1.419173e-01 B
+#> 1944 195 0.6666667 8.636116e-02 B
+#> 1945 195 0.8888889 1.198104e-02 B
+#> 1946 195 1.1111111 -4.378665e-02 B
+#> 1947 195 1.3333333 -2.603427e-01 B
+#> 1948 195 1.5555556 -4.540236e-01 B
+#> 1949 195 1.7777778 -6.285749e-01 B
+#> 1950 195 2.0000000 -9.493716e-01 B
+#> 1951 196 0.0000000 2.060538e-01 B
+#> 1952 196 0.2222222 2.464836e-01 B
+#> 1953 196 0.4444444 1.205809e-01 B
+#> 1954 196 0.6666667 6.736036e-02 B
+#> 1955 196 0.8888889 -2.242651e-02 B
+#> 1956 196 1.1111111 -1.507189e-01 B
+#> 1957 196 1.3333333 -3.808967e-01 B
+#> 1958 196 1.5555556 -5.662458e-01 B
+#> 1959 196 1.7777778 -8.743055e-01 B
+#> 1960 196 2.0000000 -1.121987e+00 B
+#> 1961 197 0.0000000 3.467559e-01 B
+#> 1962 197 0.2222222 4.536987e-01 B
+#> 1963 197 0.4444444 5.665885e-01 B
+#> 1964 197 0.6666667 4.719877e-01 B
+#> 1965 197 0.8888889 4.070098e-01 B
+#> 1966 197 1.1111111 3.843275e-01 B
+#> 1967 197 1.3333333 7.897134e-02 B
+#> 1968 197 1.5555556 6.798930e-02 B
+#> 1969 197 1.7777778 -1.321147e-01 B
+#> 1970 197 2.0000000 -2.700802e-01 B
+#> 1971 198 0.0000000 1.203713e-01 B
+#> 1972 198 0.2222222 1.451069e-01 B
+#> 1973 198 0.4444444 2.967861e-01 B
+#> 1974 198 0.6666667 1.586670e-01 B
+#> 1975 198 0.8888889 5.829574e-02 B
+#> 1976 198 1.1111111 -3.702909e-02 B
+#> 1977 198 1.3333333 -2.457303e-01 B
+#> 1978 198 1.5555556 -4.841471e-01 B
+#> 1979 198 1.7777778 -6.247883e-01 B
+#> 1980 198 2.0000000 -9.381322e-01 B
+#> 1981 199 0.0000000 2.862516e-01 B
+#> 1982 199 0.2222222 2.453220e-01 B
+#> 1983 199 0.4444444 2.517319e-01 B
+#> 1984 199 0.6666667 2.565302e-01 B
+#> 1985 199 0.8888889 8.622183e-02 B
+#> 1986 199 1.1111111 2.066621e-02 B
+#> 1987 199 1.3333333 -1.198231e-01 B
+#> 1988 199 1.5555556 -3.516931e-01 B
+#> 1989 199 1.7777778 -7.221270e-01 B
+#> 1990 199 2.0000000 -9.454804e-01 B
+#> 1991 200 0.0000000 2.123882e-01 B
+#> 1992 200 0.2222222 3.121701e-01 B
+#> 1993 200 0.4444444 3.016063e-01 B
+#> 1994 200 0.6666667 1.930413e-01 B
+#> 1995 200 0.8888889 1.780560e-01 B
+#> 1996 200 1.1111111 1.483383e-01 B
+#> 1997 200 1.3333333 -3.785807e-03 B
+#> 1998 200 1.5555556 -1.409999e-01 B
+#> 1999 200 1.7777778 -5.030799e-01 B
+#> 2000 200 2.0000000 -7.486002e-01 B
+