Package: diagis 0.2.3

Jouni Helske

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
diagis_0.2.3.tar.gz(r-4.5-noble)diagis_0.2.3.tar.gz(r-4.4-noble)
diagis_0.2.3.tgz(r-4.4-emscripten)diagis_0.2.3.tgz(r-4.3-emscripten)
diagis.pdf |diagis.html
diagis/json (API)
NEWS

# Install 'diagis' in R:
install.packages('diagis', repos = c('https://cran.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

openblascpp

2.62 score 1 packages 14 scripts 700 downloads 11 exports 32 dependencies

Last updated 1 years agofrom:68ab34cc5b. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 25 2024
R-4.5-linux-x86_64OKDec 25 2024

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 Dec 25 2024.

Last update: 2023-09-05
Started: 2016-10-29