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diagis: Diagnostic Plot and Multivariate Summary Statistics of Weighted Samples from Importance Sampling

Fast functions for effective sample size, weighted multivariate mean, variance, and quantile computation, and weight diagnostic plot for generic importance sampling type or other probability weighted samples.

Version:	0.2.3
Imports:	coda, ggplot2 (≥ 2.1.0), gridExtra, Rcpp (≥ 0.12.7)
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	covr, knitr, rmarkdown, testthat
Published:	2023-09-05
DOI:	10.32614/CRAN.package.diagis
Author:	Jouni Helske [aut, cre]
Maintainer:	Jouni Helske <jouni.helske at iki.fi>
BugReports:	https://github.com/helske/diagis/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/helske/diagis/
NeedsCompilation:	yes
Citation:	diagis citation info
Materials:	NEWS
CRAN checks:	diagis results

Documentation:

Reference manual:	diagis.pdf
Vignettes:	Auxiliary functions for importance sampling

Downloads:

Package source:	diagis_0.2.3.tar.gz
Windows binaries:	r-devel: diagis_0.2.3.zip, r-release: diagis_0.2.3.zip, r-oldrel: diagis_0.2.3.zip
macOS binaries:	r-release (arm64): diagis_0.2.3.tgz, r-oldrel (arm64): diagis_0.2.3.tgz, r-release (x86_64): diagis_0.2.3.tgz, r-oldrel (x86_64): diagis_0.2.3.tgz
Old sources:	diagis archive

Reverse dependencies:

Reverse imports:	bssm
Reverse suggests:	walker

Linking:

Please use the canonical form https://CRAN.R-project.org/package=diagis to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.