version 0.3-0

cran · Oct 22, 2017 · b59ffd0 · b59ffd0
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,33 +1,36 @@
 Package: bridgesampling
 Type: Package
 Title: Bridge Sampling for Marginal Likelihoods and Bayes Factors
-Version: 0.2-2
+Version: 0.3-0
 Authors@R: c(person(given="Quentin F.", family="Gronau", role=c("aut", "cre"),
-             email="[email protected]"), person(given="Henrik",
-             family="Singmann", role="aut"), person(given="Jonathan J.",
-             family="Forster", role="ctb"), person(given="Eric-Jan",
-             family="Wagenmakers", role="ths"), person(family="The JASP Team",
-             role="ctb"), person("Jiqiang", "Guo", role = "ctb"),
-             person("Jonah", "Gabry", role = "ctb"), person("Ben", "Goodrich", 
-             role = c("ctb")))
+             email="[email protected]",
+             comment=c(ORCID="0000-0001-5510-6943")),
+             person(given="Henrik", family="Singmann", role="aut",
+             comment=c(ORCID="0000-0002-4842-3657")),
+             person(given="Jonathan J.", family="Forster", role="ctb"),
+             person(given="Eric-Jan", family="Wagenmakers", role="ths"),
+             person(family="The JASP Team", role="ctb"),
+             person("Jiqiang", "Guo", role = "ctb"),
+             person("Jonah", "Gabry", role = "ctb"),
+             person("Ben", "Goodrich", role = c("ctb")))
 Depends: R (>= 3.0.0)
 Imports: mvtnorm, Matrix, Brobdingnag, stringr, coda, parallel, scales,
         utils, methods
-Suggests: testthat, Rcpp, RcppEigen, R2jags, knitr, rmarkdown, R.rsp,
-        BayesFactor, rstan
-Description: Provides functions for estimating marginal likelihoods, Bayes factors,
-             posterior model probabilities, and normalizing constants in general,
-             via different versions of bridge sampling (Meng & Wong, 1996,
-             <http://www3.stat.sinica.edu.tw/statistica/j6n4/j6n43/j6n43.htm>).
+Suggests: testthat, Rcpp, RcppEigen, R2jags, rjags, runjags, knitr,
+        rmarkdown, R.rsp, BayesFactor, rstan, rstanarm
+Description: Provides functions for estimating marginal likelihoods, Bayes
+    factors, posterior model probabilities, and normalizing constants in general,
+    via different versions of bridge sampling (Meng & Wong, 1996, <http://
+    www3.stat.sinica.edu.tw/statistica/j6n4/j6n43/j6n43.htm>).
 License: GPL (>= 2)
 LazyData: true
 RoxygenNote: 6.0.1
 VignetteBuilder: knitr, R.rsp
 URL: https://github.com/quentingronau/bridgesampling
 NeedsCompilation: no
-Packaged: 2017-06-26 20:31:41 UTC; henrik
-Author: Quentin F. Gronau [aut, cre],
-  Henrik Singmann [aut],
+Packaged: 2017-10-20 09:30:18 UTC; henrik
+Author: Quentin F. Gronau [aut, cre] (<https://orcid.org/0000-0001-5510-6943>),
+  Henrik Singmann [aut] (<https://orcid.org/0000-0002-4842-3657>),
   Jonathan J. Forster [ctb],
   Eric-Jan Wagenmakers [ths],
   The JASP Team [ctb],
@@ -36,4 +39,4 @@ Author: Quentin F. Gronau [aut, cre],
   Ben Goodrich [ctb]
 Maintainer: Quentin F. Gronau <[email protected]>
 Repository: CRAN
-Date/Publication: 2017-06-27 08:24:15 UTC
+Date/Publication: 2017-10-22 16:49:11 UTC
diff --git a/MD5 b/MD5
@@ -1,44 +1,55 @@
-f5259cfd58446175f8bcd473b42a17ef *DESCRIPTION
-8776b13c36d924b08d9123fdcb6bfcb7 *NAMESPACE
+0eca8898aa45e38e33119bc29f0f6538 *DESCRIPTION
+79fe5c8f5d7771077ae88677dc703c89 *NAMESPACE
 9692a5558e0d69b54fe59315629d9e1d *NEWS
-b50ec4889914e7582895c3d554a9e9fc *R/bf.R
-9647e2d2c7ae46c2e5ea7ca2b55f1ed6 *R/bridge_sampler.R
-054e94b0f2716e1c5c5712aa3dfd6670 *R/bridge_sampler_internals.R
-5f748d1773e16401cbd7f3dd094eb1fd *R/bridge_sampler_normal.R
-4e365054c8dfb7baa10d3a9e0bed72d8 *R/bridge_sampler_warp3.R
-7f74b0d5732fa9ea15c7acc4c62bded6 *R/error_measures.R
+ca0a36cd5a1d61c1ae95b8dc6aa39977 *R/bf.R
+6ea626aa11d122470af9beacfe7ff447 *R/bridge_sampler.R
+dfe66bd9723bf0a9a53e8f446f19a8b8 *R/bridge_sampler_internals.R
+f11c28c68bf3fe3e920933683f05ce6c *R/bridge_sampler_normal.R
+372ac2fae93318e481731c2007975efd *R/bridge_sampler_warp3.R
+74c06891251ab150f40a98ccf5becb24 *R/error_measures.R
+2e58141f97bc1ef12d8dac3559bec8ab *R/ier-data.R
 29219953f00413bc62ec09c800e52a82 *R/logml.R
-4c7f13d7280bc6532b16e896d6a98a49 *R/post_prob.R
-0c7824143f10e6324c16c6eb575cd4c2 *build/vignette.rds
-3b4e0cf58cabafc10438f7b271e24e24 *inst/doc/bridgesampling_example_jags.R
-3d4dd3c4a26925aad838414d420fac20 *inst/doc/bridgesampling_example_jags.Rmd
-f42e55757a6c828df1e8ec0113a1699d *inst/doc/bridgesampling_example_jags.html
+9b3d9d31efec49adbf4c2022e653709a *R/post_prob.R
+bc97086ae1bb25b528cfc88646ccc4cf *R/turtles-data.R
+966b71a33bae77823284342886b35c2e *build/vignette.rds
+0c51ed14d5576619c9f4c39aae27732a *data/ier.rda
+0fe9eaacba1bdb2098f8fdde83f65c32 *data/turtles.rda
+b423c0a78db587b8b3c2ab32a4b0c831 *inst/doc/bridgesampling_example_jags.R
+0d44dcb0a849bb62392dcc770fa86eb6 *inst/doc/bridgesampling_example_jags.Rmd
+2260db3153c55551c1cc679cb95e80bd *inst/doc/bridgesampling_example_jags.html
 53835bfe1959e3d047710615c4fefeef *inst/doc/bridgesampling_example_stan.R
 f6ee3c63d15f414dfbda31614335912c *inst/doc/bridgesampling_example_stan.Rmd
-da771e30ee48025cd7b687a84e31a916 *inst/doc/bridgesampling_example_stan.html
-38bb607f580d009d491469696f6abc1c *inst/doc/bridgesampling_stan_ttest.R
-268c3d203c62fe38b99203b135dab09c *inst/doc/bridgesampling_stan_ttest.Rmd
-b2d98dddd7670164cbcf914ca012abef *inst/doc/bridgesampling_stan_ttest.html
-f92f2238d522938e94589d5b3e3928ce *inst/doc/bridgesampling_tutorial.pdf
+c7ff881f12de59a82894f7282305d82e *inst/doc/bridgesampling_example_stan.html
+5af550d2ef1d4328d07c0127a05bda19 *inst/doc/bridgesampling_paper.pdf
+cae5f6b91b56445d6d8185ee6d9bd5cd *inst/doc/bridgesampling_paper.pdf.asis
+ac6a46f89e285f5674c6a00f8ae8ee25 *inst/doc/bridgesampling_stan_ttest.R
+86336d310d665c7001be2b0a832e723c *inst/doc/bridgesampling_stan_ttest.Rmd
+43a8f58c0d8d4474283a0b48d5e3f359 *inst/doc/bridgesampling_stan_ttest.html
+b05e71afec129b7e02e02978eb679d5b *inst/doc/bridgesampling_tutorial.pdf
 0975f714b581ed709f0a23ae6cb5cb4d *inst/doc/bridgesampling_tutorial.pdf.asis
-18f418f029251e655d0972e4856616e5 *man/bf.Rd
-5f208595e2470e1e3fec94a5cdb1a784 *man/bridge_sampler.Rd
-354147533f54d3c409795a272730b21e *man/error_measures.Rd
+012b07ba0a9a95b138f776a5f28cc798 *man/bf.Rd
+7d9d10e2a484dd21f361a5bf6f8644bb *man/bridge_sampler.Rd
+ff7e388e306429278ceeb62d0459f0fc *man/error_measures.Rd
+9ef82c96e8210238a41fd7f312944b99 *man/ier.Rd
 89434ad340ebd3a1c54c6004e3050c87 *man/logml.Rd
-f686f21d77c18716603c23768e829568 *man/post_prob.Rd
+044d385495df7f4ec5f18daeeba81586 *man/post_prob.Rd
+d7259e27e5fc8c60a848c047bf2aac42 *man/turtles.Rd
 9d667770b4162f1cc0ffb5c78385fbac *tests/testthat.R
-98ccba6751861e2ccb351eca05dba7c9 *tests/testthat/test-bf_print_method.R
-591c457ef4698679065c69c4792c588d *tests/testthat/test-bridge_sampler_normal.R
-1a1152b3a489c791a0cd87ef6a0db3f3 *tests/testthat/test-bridge_sampler_normal_Rcpp.R
-14a56f0ffebe30b2218969306199b073 *tests/testthat/test-bridge_sampler_normal_Rcpp_parallel.R
-1905b17e96f690d5e030cff86d9a8330 *tests/testthat/test-bridge_sampler_normal_parallel.R
+fefe19c39a4fe131b15334aae8891a14 *tests/testthat/test-bf_print_method.R
+591c457ef4698679065c69c4792c588d *tests/testthat/test-bridge_sampler.R
+1a1152b3a489c791a0cd87ef6a0db3f3 *tests/testthat/test-bridge_sampler_Rcpp.R
+14a56f0ffebe30b2218969306199b073 *tests/testthat/test-bridge_sampler_Rcpp_parallel.R
+e2fbd39be6fb31325ce321f8eb538d1c *tests/testthat/test-bridge_sampler_mcmc.list.R
+1905b17e96f690d5e030cff86d9a8330 *tests/testthat/test-bridge_sampler_parallel.R
 1766960472cb0d775ffe291127d5686b *tests/testthat/test-bridge_sampler_print_method.R
 73f79e1aa83a59a1c2d9df90e038656c *tests/testthat/test-post_prob.R
-66a3fec0b90161b82b5176c938c85ded *tests/testthat/test-stan_bridge_sampler_basic.R
-dfd2998bc5aeaa7b30fc96192155fbbb *tests/testthat/test-stan_bridge_sampler_bugs.R
+b7225937c6f82db5b2ed9e9be4ed8331 *tests/testthat/test-stan_bridge_sampler_basic.R
+0508d17f1cc088a689dc525d7732f781 *tests/testthat/test-stan_bridge_sampler_bugs.R
+8d44f6e353cbaf3ac5498132f6766f87 *tests/testthat/test-stanreg_bridge_sampler_basic.R
 6e8d98c9521d5c6c0e7fad8fdfc5d801 *tests/testthat/unnormalized_normal_density.cpp
 ef671e9eb9ca452eae9d3a91202514ce *tests/testthat/unnormalized_normal_density_mu.cpp
-3d4dd3c4a26925aad838414d420fac20 *vignettes/bridgesampling_example_jags.Rmd
+0d44dcb0a849bb62392dcc770fa86eb6 *vignettes/bridgesampling_example_jags.Rmd
 f6ee3c63d15f414dfbda31614335912c *vignettes/bridgesampling_example_stan.Rmd
-268c3d203c62fe38b99203b135dab09c *vignettes/bridgesampling_stan_ttest.Rmd
+cae5f6b91b56445d6d8185ee6d9bd5cd *vignettes/bridgesampling_paper.pdf.asis
+86336d310d665c7001be2b0a832e723c *vignettes/bridgesampling_stan_ttest.Rmd
 0975f714b581ed709f0a23ae6cb5cb4d *vignettes/bridgesampling_tutorial.pdf.asis
diff --git a/NAMESPACE b/NAMESPACE
@@ -1,10 +1,15 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(bayes_factor,default)
 S3method(bf,bridge)
 S3method(bf,bridge_list)
 S3method(bf,default)
 S3method(bridge_sampler,matrix)
+S3method(bridge_sampler,mcmc.list)
+S3method(bridge_sampler,rjags)
+S3method(bridge_sampler,runjags)
 S3method(bridge_sampler,stanfit)
+S3method(bridge_sampler,stanreg)
 S3method(logml,bridge)
 S3method(logml,bridge_list)
 S3method(post_prob,bridge)
@@ -15,6 +20,7 @@ S3method(print,bf_bridge_list)
 S3method(print,bf_default)
 S3method(print,bridge)
 S3method(print,bridge_list)
+export(bayes_factor)
 export(bf)
 export(bridge_sampler)
 export(error_measures)
@@ -33,3 +39,4 @@ importFrom(stats,pnorm)
 importFrom(stats,qnorm)
 importFrom(stats,var)
 importFrom(stringr,str_sub)
+importFrom(utils,read.csv)
diff --git a/R/bf.R b/R/bf.R
@@ -1,9 +1,10 @@
-#" Generic function that computes Bayes factor(s) from marginal likelihoods.
+#" Generic function that computes Bayes factor(s) from marginal likelihoods. \code{bayes_factor()} is simply an (S3 generic) alias for \code{bf()}.
 #' @export
 #' @title Bayes Factor(s) from Marginal Likelihoods
 #' @param x1 Object of class \code{"bridge"} or \code{"bridge_list"} as returned from \code{\link{bridge_sampler}}. Additionally, the default method assumes that \code{x1} is a single numeric log marginal likelihood (e.g., from \code{\link{logml}}) and will throw an error otherwise.
 #' @param x2 Object of class \code{"bridge"} or \code{"bridge_list"} as returned from \code{\link{bridge_sampler}}. Additionally, the default method assumes that \code{x2} is a single numeric log marginal likelihood (e.g., from \code{\link{logml}}) and will throw an error otherwise.
 #' @param log Boolean. If \code{TRUE}, the function returns the log of the Bayes factor. Default is \code{FALSE}.
+#' @param ... currently not used here, but can be used by other methods.
 #' @details Computes the Bayes factor (Kass & Raftery, 1995) in favor of the model associated with \code{x1} over the model associated with \code{x2}.
 #' @return For the default method returns a list of class \code{"bf_default"} with components:
 #' \itemize{
@@ -26,14 +27,28 @@
 #'  \item \code{log}: Boolean which indicates whether \code{bf} corresponds to the log Bayes factor.
 #' }
 #' @author Quentin F. Gronau
-#" @note For examples, see \code{\link{bridge_sampler}} and the accompanying vignette: \cr \code{vignette("bridgesampling_example")}
+#" @note For examples, see \code{\link{bridge_sampler}} and the accompanying vignettes: \cr \code{vignette("bridgesampling_example_jags")} \cr \code{vignette("bridgesampling_example_stan")}
 #' @references
-#" Kass, R. E., & Raftery, A. E. (1995). Bayes factors. \emph{Journal of the American Statistical Association}, 90(430), 773-795. \url{http://dx.doi.org/10.1080/01621459.1995.10476572}
+#" Kass, R. E., & Raftery, A. E. (1995). Bayes factors. \emph{Journal of the American Statistical Association, 90(430)}, 773-795. \url{http://dx.doi.org/10.1080/01621459.1995.10476572}
 #' @importFrom methods is
-bf <- function(x1, x2, log = FALSE) {
+bf <- function(x1, x2, log = FALSE, ...) {
   UseMethod("bf", x1)
 }
 
+#' @rdname bf
+#' @export
+bayes_factor <- function(x1, x2, log = FALSE, ...) {
+  UseMethod("bayes_factor", x1)
+}
+
+
+#' @rdname bf
+#' @export
+bayes_factor.default <- function(x1, x2, log = FALSE, ...) {
+  bf(x1, x2, log = log, ...)
+}
+
+
 .bf_calc <- function(logml1, logml2, log) {
   bf <- logml1 - logml2
   if (! log)
@@ -43,7 +58,9 @@ bf <- function(x1, x2, log = FALSE) {
 
 #' @rdname bf
 #' @export
-bf.bridge <- function(x1, x2, log = FALSE) {
+bf.bridge <- function(x1, x2, log = FALSE, ...) {
+  #name1 <- as.character(match.call()[[2]])
+  #name2 <- as.character(match.call()[[3]])
   bf <- .bf_calc(logml(x1), logml(x2), log = log)
   out <- list(bf = bf, log = log)
   class(out) <- "bf_bridge"
@@ -53,7 +70,7 @@ bf.bridge <- function(x1, x2, log = FALSE) {
 
 #' @rdname bf
 #' @export
-bf.bridge_list <- function(x1, x2, log = FALSE) {
+bf.bridge_list <- function(x1, x2, log = FALSE, ...) {
   logml1 <- x1$logml
   logml2 <- x2$logml
   median1 <- median(logml1, na.rm = TRUE)
@@ -75,7 +92,7 @@ bf.bridge_list <- function(x1, x2, log = FALSE) {
 
 #' @rdname bf
 #' @export
-bf.default <- function(x1, x2, log = FALSE) {
+bf.default <- function(x1, x2, log = FALSE, ...) {
   if (!is.numeric(c(x1, x2))) {
     stop("logml values need to be numeric", call. = FALSE)
   }
@@ -94,23 +111,23 @@ bf.default <- function(x1, x2, log = FALSE) {
 #' @export
 print.bf_bridge <- function(x, ...) {
   if (x$log) {
-    cat("The estimated log Bayes factor is equal to: ", round(x$bf, 5), sep = "")
+    cat("The estimated log Bayes factor in favor of x1 over x2 is equal to: ", round(x$bf, 5), sep = "")
   } else if (! x$log) {
-    cat("The estimated Bayes factor is equal to: ", round(x$bf, 5), sep = "")
+    cat("The estimated Bayes factor in favor of x1 over x2 is equal to: ", round(x$bf, 5), sep = "")
   }
 }
 
 #' @method print bf_bridge_list
 #' @export
 print.bf_bridge_list <- function(x, na.rm = TRUE,...) {
   if (x$log) {
-    cat("The estimated log Bayes factor (based on the medians of the log marginal likelihood estimates) is equal to: ",
+    cat("The estimated log Bayes factor in favor of x1 over x2 (based on the medians of the log marginal likelihood estimates) is equal to: ",
         round(x$bf_median_based, 5), "\nRange of estimates: ", round(range(x$bf, na.rm=na.rm)[1], 5), " to ",
         round(range(x$bf, na.rm = na.rm)[2], 5),
         "\nInterquartile range: ", round(stats::IQR(x$bf, na.rm = na.rm), 5), sep = "")
     if (any(is.na(x$bf))) warning(sum(is.na(x$bf))," log Bayes factor estimate(s) are NAs.", call. = FALSE)
   } else if (! x$log) {
-    cat("The estimated Bayes factor (based on the medians of the log marginal likelihood estimates) is equal to: ",
+    cat("The estimated Bayes factor in favor of x1 over x2 (based on the medians of the log marginal likelihood estimates) is equal to: ",
         round(x$bf_median_based, 5), "\nRange of estimates: ", round(range(x$bf, na.rm=na.rm)[1], 5), " to ",
         round(range(x$bf, na.rm = na.rm)[2], 5),
         "\nInterquartile range: ", round(stats::IQR(x$bf, na.rm = na.rm), 5), sep = "")
@@ -122,8 +139,8 @@ print.bf_bridge_list <- function(x, na.rm = TRUE,...) {
 #' @export
 print.bf_default <- function(x, ...) {
   if (x$log) {
-    cat("The log Bayes factor is equal to: ", round(x$bf, 5), sep = "")
+    cat("The log Bayes factor in favor of x1 over x2 is equal to: ", round(x$bf, 5), sep = "")
   } else if (! x$log) {
-    cat("The Bayes factor is equal to: ", round(x$bf, 5), sep = "")
+    cat("The Bayes factor in favor of x1 over x2 is equal to: ", round(x$bf, 5), sep = "")
   }
 }