Package: diagis 0.2.3

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.

Authors:Jouni Helske [aut, cre]

diagis_0.2.3.tar.gz
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diagis.pdf |diagis.html
diagis/json (API)
NEWS

# Install 'diagis' in R:
install.packages('diagis', repos = c('https://helske.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/helske/diagis/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

cppimportance-samplingweighted-samplesopenblascpp

4.32 score 1 stars 1 packages 14 scripts 643 downloads 11 exports 32 dependencies

Last updated 1 years agofrom:ae13f60638. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 05 2025
R-4.5-win-x86_64OKJan 05 2025
R-4.5-linux-x86_64OKJan 05 2025
R-4.4-win-x86_64OKJan 05 2025
R-4.4-mac-x86_64OKJan 05 2025
R-4.4-mac-aarch64OKJan 05 2025
R-4.3-win-x86_64OKJan 05 2025
R-4.3-mac-x86_64OKJan 05 2025
R-4.3-mac-aarch64OKJan 05 2025

Exports:essrunning_essrunning_meanrunning_varrunning_weighted_meanrunning_weighted_varweight_plotweighted_meanweighted_quantileweighted_seweighted_var

Dependencies:clicodacolorspacefansifarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr

diagis: Diagnostic plot and multivariate summary statistics of weighted samples from importance sampling

Rendered fromdiagis.Rmdusingknitr::rmarkdownon Jan 05 2025.

Last update: 2021-11-15
Started: 2016-10-27