## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, eval = FALSE) ## ----------------------------------------------------------------------------- # library(BayesRTMB) # data(debate) # # mdl <- rtmb_lm(sat ~ talk * perf, data = debate) ## ----------------------------------------------------------------------------- # fit_mcmc <- mdl$sample() # fit_map <- mdl$optimize() # fit_cl <- mdl$classic() ## ----------------------------------------------------------------------------- # mdl <- rtmb_lm(sat ~ talk * perf, data = debate) # fit <- mdl$sample() # fit$summary() ## ----------------------------------------------------------------------------- # fit <- mdl$optimize() # fit$summary() ## ----------------------------------------------------------------------------- # fit <- mdl$classic() # fit$summary() ## ----------------------------------------------------------------------------- # rtmb_corr(cbind(sat, perf), data = debate)$classic() ## ----------------------------------------------------------------------------- # rtmb_corr(cbind(sat, perf), # data = debate, # covariates = ~ skill)$classic() ## ----------------------------------------------------------------------------- # rtmb_corr(cbind(sat, perf), data = debate, method = "spearman")$classic() # rtmb_corr(cbind(sat, perf), data = debate, method = "reml")$classic() ## ----------------------------------------------------------------------------- # fit_tab <- rtmb_table(skill, cond, data = debate)$classic() # anova(fit_tab) ## ----------------------------------------------------------------------------- # data(BigFive) # # items <- BigFive[, 1:10] # fit_fa1 <- rtmb_fa(items, nfactors = 1)$classic() # fit_fa2 <- rtmb_fa(items, nfactors = 2)$classic() # # anova(fit_fa1, fit_fa2) ## ----------------------------------------------------------------------------- # c(AIC_1 = AIC(fit_fa1), # AIC_2 = AIC(fit_fa2), # BIC_1 = BIC(fit_fa1), # BIC_2 = BIC(fit_fa2)) ## ----------------------------------------------------------------------------- # mdl <- rtmb_ttest(sat ~ cond, data = debate) # mdl$print_code()