R Under development (unstable) (2024-04-23 r86473 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(epigrowthfit) > library(tools) > options(warn = 2L, error = if (interactive()) recover) > > > ## Normal ############################################################## > > mu <- rnorm(10L) > sigma <- rlnorm(5L) > > stopifnot(identical(Normal(mu = mu, sigma = sigma), + structure(list(family = "norm", + parameters = list(mu = mu, sigma = sigma)), + class = "egf_prior"))) > > assertError(Normal(mu = "1", sigma = sigma)) > assertError(Normal(mu = double(0L), sigma = sigma)) > assertError(Normal(mu = NaN, sigma = sigma)) > assertError(Normal(mu = Inf, sigma = sigma)) > assertError(Normal(mu = mu, sigma = "1")) > assertError(Normal(mu = mu, sigma = double(0L))) > assertError(Normal(mu = mu, sigma = NaN)) > assertError(Normal(mu = mu, sigma = Inf)) > assertError(Normal(mu = mu, sigma = 0)) > assertError(Normal(mu = mu, sigma = -1)) > > > ## LKJ ################################################################# > > eta <- c(0.1, 1, 10) > > stopifnot(identical(LKJ(eta = eta), + structure(list(family = "lkj", + parameters = list(eta = eta)), + class = "egf_prior"))) > > assertError(LKJ(eta = "1")) > assertError(LKJ(eta = double(0L))) > assertError(LKJ(eta = NaN)) > assertError(LKJ(eta = Inf)) > assertError(LKJ(eta = 0)) > assertError(LKJ(eta = -1)) > > > ## (Inverse)?Wishart ################################################### > > set.seed(230719L) > n <- 4L > A <- matrix(rnorm(n * n), n, n) > S <- crossprod(A) > R <- chol(S) > R1 <- R * rep(1 / diag(R, names = FALSE), each = n) > > df <- 8 > theta <- c(0.5 * log(diag(S, names = FALSE)), R1[upper.tri(R1)]) > prior <- + structure(list(family = NA_character_, + parameters = list(df = df, scale = list(theta))), + class = "egf_prior") > > stopifnot(exprs = { + identical( Wishart(df = df, scale = list(S)), + replace(prior, "family", list( "wishart"))) + identical(InverseWishart(df = df, scale = list(S)), + replace(prior, "family", list("invwishart"))) + }) > > assertError(Wishart(df = 3, scale = S)) > assertError(Wishart(df = df, scale = A)) > assertError(Wishart(df = df, scale = diag(0, n))) > > proc.time() user system elapsed 1.09 0.25 1.32