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z%;NWY`G93qbl%1}eY~#{h5%i?Cwg)M8UKoC!9<0HI*8~ZYN5MW*Im?gibxmVb`N|f z&(6<>G!*C)KAoEwd4VRM1hE{TlVO`eocR;n$vICy)d{MdkZ&XGhT-%I^YWs!Hzm87td8*({dsdUQ^11d{gey2?y z-D-Dv6eGHk}?c@PT3)ezaK<6Zy P399x#&z(FW1HKyowZEon diff --git a/inst/extdata/run_examples.R b/inst/extdata/run_examples.R index 6ed54dc..c37d586 100644 --- a/inst/extdata/run_examples.R +++ b/inst/extdata/run_examples.R @@ -220,8 +220,20 @@ if (run_brms) { iter=200) brms_RE <- hack_size(brms_RE) + # Example taken from ?brms::brm + ## Probit regression using the binomial family + ntrials <- sample(1:10, 100, TRUE) + success <- rbinom(100, size = ntrials, prob = 0.4) + x <- rnorm(100) + data4 <- data.frame(ntrials, success, x) + fit4 <- brm(success | trials(ntrials) ~ x, data = data4, + family = binomial("probit")) + brms_brm_fit4 <- hack_size(fit4) + + save_file(brms_crossedRE, brms_zip, brms_multi, brms_noran, - brms_multi_RE, brms_RE, pkg = pkg, type = "rda") + brms_multi_RE, brms_RE, brms_brm_fit4, + pkg = pkg, type = "rda") }) } From a3ba632aacd2f540ed0aa0737f2cc107ed508787 Mon Sep 17 00:00:00 2001 From: Matthieu Bruneaux Date: Sun, 24 Dec 2023 20:51:07 +0200 Subject: [PATCH 2/3] Add tests for some columns of tidy.brmsfit() output --- tests/testthat/test-brms.R | 32 ++++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) diff --git a/tests/testthat/test-brms.R b/tests/testthat/test-brms.R index e1c259b..b659116 100644 --- a/tests/testthat/test-brms.R +++ b/tests/testthat/test-brms.R @@ -17,4 +17,36 @@ if (require(brms, quietly = TRUE) && require(rstanarm, quietly=TRUE)) { ## GH #101 gg <- glance(brms_noran) expect_equal(names(gg),c("algorithm","pss","nobs","sigma")) + + ## Check the descriptive columns of tidy summaries + ### brms_RE + expected <- tibble::tribble( + ~effect, ~component, ~group, ~term, + "fixed", "cond", NA, "(Intercept)", + "fixed", "cond", NA, "Days_extra", + "ran_pars", "cond", "Subject", "sd__(Intercept)", + "ran_pars", "cond", "Subject", "sd__Days_extra", + "ran_pars", "cond", "Subject", "cor__(Intercept).Days_extra", + "ran_pars", "cond", "Residual", "sd__Observation" + ) + observed <- suppressWarnings(tidy(brms_RE)) + expect_equal(observed[, 1:4], expected) + ### brms_noran + expected <- tibble::tribble( + ~effect, ~component, ~group, ~term, + "fixed", "cond", NA, "(Intercept)", + "fixed", "cond", NA, "wt", + "ran_pars", "cond", "Residual", "sd__Observation" + ) + observed <- suppressWarnings(tidy(brms_noran)) + expect_equal(observed[, 1:4], expected) + ### brms_brm_fit4 + expected <- tibble::tribble( + ~effect, ~component, ~group, ~term, + "fixed", "cond", NA, "(Intercept)", + "fixed", "cond", NA, "x" + ) + observed <- suppressWarnings(tidy(brms_brm_fit4)) + expect_equal(observed[, 1:4], expected) + } From f17e221523b29e2cf4a70d7d891a72665ac4ea63 Mon Sep 17 00:00:00 2001 From: Matthieu Bruneaux Date: Sun, 24 Dec 2023 20:55:46 +0200 Subject: [PATCH 3/3] Fix tidy.brmsfit() formatting of group and term columns --- R/brms_tidiers.R | 16 ++++++++++++---- 1 file changed, 12 insertions(+), 4 deletions(-) diff --git a/R/brms_tidiers.R b/R/brms_tidiers.R index 1ab34a8..a295440 100644 --- a/R/brms_tidiers.R +++ b/R/brms_tidiers.R @@ -137,14 +137,14 @@ tidy.brmsfit <- function(x, parameters = NA, ## don't want to remove these pieces, so use look*behind* ran_pars = sprintf("(?<=(%s))", c("sd_", "cor_", "sigma")), components = sprintf("(?<=%s)", c("zi_","disp_")) - ) - prefs <- list( + ) + prefs <- list( fixed = "b_", ran_vals = "r_", ## no lookahead (doesn't work with grep[l]) ran_pars = c("sd_", "cor_", "sigma"), components = c("zi_", "disp_") - ) - pref_RE <- mkRE(prefs[effects]) + ) + pref_RE <- mkRE(prefs[effects]) if (use_effects) { ## prefixes distinguishing fixed, random effects @@ -240,6 +240,14 @@ tidy.brmsfit <- function(x, parameters = NA, } out <- dplyr::bind_rows(res_list, .id = "effect") + # In the case where nrow(res_list$fixed) > 0 but nrow(res_list$ran_pars) == 0, + # the out object needs to be fixed a bit (replace columns with unexpected + # lists of NULL by expected vectors of NA). + for (col in c("group", "term")) { + if (is.list(out[[col]]) && all(sapply(out[[col]], is.null))) { + out[[col]] <- rep(NA, nrow(out)) + } + } v <- if (fixed.only) seq(nrow(out)) else is.na(out$term) newterms <- stringr::str_remove(terms[v], mkRE(prefs[c("fixed")])) if (fixed.only) {

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