version 3.1.0

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mcmcensemble
 Title: Ensemble Sampler for Affine-Invariant MCMC
-Version: 3.0.0
+Version: 3.1.0
 Authors@R: 
     c(person(given = "Hugo",
              family = "Gruson",
@@ -21,23 +21,24 @@ Description: Provides ensemble samplers for
     Vrugt (2008) <doi:10.1007/s11222-008-9104-9> and the 'stretch' sampler
     from Goodman and Weare (2010) <doi:10.2140/camcos.2010.5.65>.
 License: GPL-2
-URL: https://github.com/Bisaloo/mcmcensemble,
-        https://bisaloo.github.io/mcmcensemble/
+URL: https://hugogruson.fr/mcmcensemble/,
+        https://github.com/Bisaloo/mcmcensemble
 BugReports: https://github.com/Bisaloo/mcmcensemble/issues
 Depends: R (>= 3.5)
 Imports: future.apply, progressr
 Suggests: bayesplot, coda, mockery, testthat (>= 3.0.0), knitr,
         rmarkdown
 Encoding: UTF-8
-RoxygenNote: 7.1.1.9001
+RoxygenNote: 7.3.1
 Config/testthat/edition: 3
+Config/Needs/website: r-for-educators/flair, spacefillr
 VignetteBuilder: knitr
 NeedsCompilation: no
-Packaged: 2021-04-27 11:29:41 UTC; hugo
+Packaged: 2024-03-20 16:28:45 UTC; hugo
 Author: Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>),
   Sanda Dejanic [aut, cph],
   Andreas Scheidegger [aut, cph]
     (<https://orcid.org/0000-0003-2575-2172>)
 Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>
 Repository: CRAN
-Date/Publication: 2021-04-28 13:20:03 UTC
+Date/Publication: 2024-03-20 16:50:02 UTC

MD5

@@ -1,26 +1,26 @@
-e4ee17a6f62b60df0e71bb4ed31a4db3 *DESCRIPTION
+0aa0328799ce412a62068ca79d85dcbe *DESCRIPTION
 9c2c7cff5a3b7d6e1fe516aa5747affd *NAMESPACE
-fee967acc45d63a5b6bd3fa59d42c257 *NEWS.md
-048b9761aec9d50889b902f74123d5b4 *R/MCMCEnsemble.R
+1cf1e9aefa09e40f35eaccae62dc89d1 *NEWS.md
+a2a6f7313e718419333dd195724783e0 *R/MCMCEnsemble.R
 e8c53d179790dd7584119ac16b3f219f *R/d.e.mcmc.R
 5a2436fe6a4782d4b94f91bf9ee820ce *R/mcmcensemble-package.R
 543a7ee1ac889238b12310a9ea073b2c *R/s.m.mcmc.R
-974160b497bfe889ce6ba8ae41e3ad54 *README.md
-65d78eb69e91703cba2eab4fd9bfa082 *build/partial.rdb
-86da373324105b3cedc6a7d59077a8f6 *build/vignette.rds
-2d3e2ffb842514a2c7c5fa0fb819cd44 *inst/doc/diagnostic-pkgs.R
+ad17cd28a481dd76704222c23645ea2c *README.md
+20c8d3f97d93e2e318a22508275b5a02 *build/partial.rdb
+430b80a90aeb2d3b04934506d8b581eb *build/vignette.rds
+cddf28d7da8ee2aebfb04cb47b60cdb5 *inst/doc/diagnostic-pkgs.R
 06e526aa4bff5bf030df2efe4d09eaee *inst/doc/diagnostic-pkgs.Rmd
-be8c3b10f921c139db2a059ee757cdce *inst/doc/diagnostic-pkgs.html
-90da8166157ac5a2daa6bec350e67de7 *inst/doc/faq.R
-ac79f1694fce4ba35d534524772b5018 *inst/doc/faq.Rmd
-a06a2c05df5f97123cefddeb0839d76b *inst/doc/faq.html
-2429f4d9e58825fab069450b791c7282 *man/MCMCEnsemble.Rd
-6cb5440ef7a0069a18d1a57659643b5e *man/figures/README-example-de-1.svg
-c19a74594d7c62a484f0f18daf6b40bf *man/figures/README-example-stretch-1.svg
-23c04d0dcaf80725c567cfb046b801ab *man/mcmcensemble-package.Rd
+bc4cd4af1b69f1935aa642367cc63402 *inst/doc/diagnostic-pkgs.html
+07409e187a5c8bd92959cf661b4350d0 *inst/doc/faq.R
+1bf3e7f34096ec719d9e96b8a6402a27 *inst/doc/faq.Rmd
+082d29977c547f0d3f0880f7630d319c *inst/doc/faq.html
+0a53dd2af9e9d87a5103e25e435c69d5 *man/MCMCEnsemble.Rd
+5f10a09c9e6a5d026d5283cf1c155a7c *man/figures/README-example-de-1.svg
+1ddbbede6988ce2c519230880a97fd53 *man/figures/README-example-stretch-1.svg
+76ba62b4cc601d1ec9e2556f8ee53c71 *man/mcmcensemble-package.Rd
 1495e1617d4670efb997b4dc2f4717f2 *tests/testthat.R
-23b45d862066c010e38650d31bc7f365 *tests/testthat/test-MCMCEnsemble.R
+814f8afcf2bb313518ab775904451310 *tests/testthat/test-MCMCEnsemble.R
 5afbe2390b9ac12284e3667a2a578fcf *tests/testthat/test-convergence.R
 78f2ab105798e2b132ce325f85457f57 *vignettes/blog/blog_v3.Rmd
 06e526aa4bff5bf030df2efe4d09eaee *vignettes/diagnostic-pkgs.Rmd
-ac79f1694fce4ba35d534524772b5018 *vignettes/faq.Rmd
+1bf3e7f34096ec719d9e96b8a6402a27 *vignettes/faq.Rmd

NEWS.md

@@ -1,3 +1,11 @@
+# mcmcensemble 3.1.0
+
+## Minor improvements
+
+* there is now a clearer error message when trying to use a single walker since
+ensemble sampling is designed to work with multiple walkers (#6 by @Bisaloo,
+based on a report from @adamkucharski).
+
 # mcmcensemble 3.0.0
 
 ## Major changes
@@ -49,7 +57,7 @@ an additional attribute (accessible via `attr(res, "ensemble.sampler")`).
 ## Major changes
 
 * the ensemble sampling can now be parallelised with the future framework. Check
-the [README](https://bisaloo.github.io/mcmcensemble/) for more information
+the [README](https://hugogruson.fr/mcmcensemble/) for more information
 
 ## Other user-facing changes
 

R/MCMCEnsemble.R

@@ -10,7 +10,8 @@
 #' @param inits A matrix (or data.frame) containing the starting values for the
 #'   walkers. Each column is a variable to estimate and each row is a walker
 #' @param max.iter maximum number of function evaluations
-#' @param n.walkers number of walkers (ensemble size)
+#' @param n.walkers number of walkers (ensemble size). An integer greater or
+#'   equal than 2.
 #' @param method method for proposal generation, either `"stretch"`, or
 #'   `"differential.evolution"`. This argument will be saved as an attribute
 #'   in the output (see examples).
@@ -97,6 +98,10 @@ MCMCEnsemble <- function(f, inits, max.iter, n.walkers = 10 * ncol(inits),
     inits <- as.matrix(inits)
   }
 
+  if (n.walkers < 2) {
+    stop("The number of walkers must be at least 2", call. = FALSE)
+  }
+
   if (nrow(inits) != n.walkers) {
     stop(
       "The number of rows of `inits` must be equal to `n.walkers`",

README.md

@@ -10,17 +10,16 @@ status](https://www.r-pkg.org/badges/version-ago/mcmcensemble)](https://CRAN.R-p
 [![R build
 status](https://github.com/Bisaloo/mcmcensemble/workflows/R-CMD-check/badge.svg)](https://github.com/Bisaloo/mcmcensemble/actions)
 [![Codecov test
-coverage](https://codecov.io/gh/Bisaloo/mcmcensemble/branch/master/graph/badge.svg)](https://codecov.io/gh/Bisaloo/mcmcensemble?branch=master)
+coverage](https://codecov.io/gh/Bisaloo/mcmcensemble/branch/main/graph/badge.svg)](https://app.codecov.io/gh/Bisaloo/mcmcensemble?branch=main)
 [![Lifecycle:
 stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
 
 This R package provides ensemble samplers for affine-invariant Monte
 Carlo Markov Chain, which allow a faster convergence for badly scaled
 estimation problems. Two samplers are proposed: the
-‘differential.evolution’ sampler from [ter Braak and
-Vrugt](#ref-terBraak2008) ([2008](#ref-terBraak2008)) and the ‘stretch’
-sampler from [Goodman and Weare](#ref-Goodman2010)
-([2010](#ref-Goodman2010)).
+‘differential.evolution’ sampler from ter Braak and Vrugt
+([2008](#ref-terBraak2008)) and the ‘stretch’ sampler from Goodman and
+Weare ([2010](#ref-Goodman2010)).
 
 For theoretical background about Ensemble MCMC (what are the benefits
 over simple MCMC? How do they work? What are the pitfalls?), please
@@ -37,7 +36,7 @@ install.packages("mcmcensemble")
 ```
 
 or the development version from [GitHub](https://github.com/bisaloo),
-via my [r-universe](https://bisaloo.r-universe.dev/):
+via my [r-universe](https://bisaloo.r-universe.dev/packages):
 
 ``` r
 install.packages("mcmcensemble", repos = "https://bisaloo.r-universe.dev")
@@ -119,6 +118,11 @@ summary(res2$samples)
 #> a -19.563 -8.1257 -1.429 4.862 13.448
 #> b  -8.809 -0.7837  1.199 2.519  4.225
 plot(res2$samples)
+#> Warning in rep(col, length = nchain(x)): partial argument match of 'length' to
+#> 'length.out'
+
+#> Warning in rep(col, length = nchain(x)): partial argument match of 'length' to
+#> 'length.out'
 ```
 
 <img src="man/figures/README-example-stretch-1.svg" width="100%" />
@@ -153,13 +157,18 @@ summary(res3$samples)
 #> a -23.87 -6.4298 -0.2157 6.038 16.33
 #> b -13.53 -0.8687  1.6170 2.583  4.22
 plot(res3$samples)
+#> Warning in rep(col, length = nchain(x)): partial argument match of 'length' to
+#> 'length.out'
+
+#> Warning in rep(col, length = nchain(x)): partial argument match of 'length' to
+#> 'length.out'
 ```
 
 <img src="man/figures/README-example-de-1.svg" width="100%" />
 
 To see more plotting and MCMC diagnostic options, please refer to the
 relevant vignette:
-[`vignette("diagnostic-pkgs", package = "mcmcensemble")`](https://bisaloo.github.io/mcmcensemble/articles/diagnostic-pkgs.html)
+[`vignette("diagnostic-pkgs", package = "mcmcensemble")`](https://hugogruson.fr/mcmcensemble/articles/diagnostic-pkgs.html)
 
 ## Progress bar
 
@@ -193,20 +202,20 @@ at the start of your session.
 ## Similar projects
 
 The Goodman-Weare ‘stretch’ sampler is also available in the [tonic R
-package](https://github.com/svdataman/tonic).
+package](https://github.com/SimonVaughanDataAndCode/tonic).
 
 The methods used in this package also have (independent) implementations
 in other languages:
 
--   [emcee v3: A Python ensemble sampling toolkit for affine-invariant
-    MCMC](https://doi.org/10.21105/joss.01864)
--   [GWMCMC which implements the Goodman-Weare ‘stretch’ sampler in
-    Matlab](https://github.com/grinsted/gwmcmc)
+- [emcee v3: A Python ensemble sampling toolkit for affine-invariant
+  MCMC](https://doi.org/10.21105/joss.01864)
+- [GWMCMC which implements the Goodman-Weare ‘stretch’ sampler in
+  Matlab](https://github.com/grinsted/gwmcmc)
 
 ## Who is talking about this package?
 
--   [R View from October
-    2020](https://rviews.rstudio.com/2020/11/19/october-2020-top-40-new-cran-packages/)
+- [R View from October
+  2020](https://rviews.rstudio.com/2020/11/19/october-2020-top-40-new-cran-packages/)
 
 ## References
 

inst/doc/diagnostic-pkgs.R

@@ -1,4 +1,4 @@
-## ---- include = FALSE---------------------------------------------------------
+## ----include = FALSE----------------------------------------------------------
 knitr::opts_chunk$set(
   collapse = TRUE,
   comment = "#>"
@@ -36,7 +36,7 @@ class(res$samples)
 ## -----------------------------------------------------------------------------
 summary(res$samples)
 
-## ---- eval = identical(Sys.getenv("IN_PKGDOWN"), "true")----------------------
+## ----eval = identical(Sys.getenv("IN_PKGDOWN"), "true")-----------------------
 #  plot(res$samples)
 
 ## -----------------------------------------------------------------------------
@@ -58,7 +58,7 @@ res_coda <- MCMCEnsemble(
   max.iter = 3000, n.walkers = 10, method = "stretch", coda = TRUE
 )
 
-## ---- out.width='45%', fig.show='hold'----------------------------------------
+## ----out.width='45%', fig.show='hold'-----------------------------------------
 # Density of log-posterior of each parameter
 mcmc_areas(res_nocoda$samples)
 mcmc_areas(res_coda$samples)