Package: logcumulant 0.1.0

logcumulant: Goodness-of-Fit Tests and Diagrams Based on Mellin Log-Cumulants

A family of three complementary goodness-of-fit tests based on an adaptation of Hotelling's T-squared statistic applied to vectors of sample log-cumulants (Mellin statistics) for positive-support reliability data. The package provides the asymptotic chi-squared reference and parametric bootstrap p-values for reliable finite-sample inference, covering the Weibull, Frechet, Gamma, Inverse-Gamma, Log-Normal, and Log-Logistic families. It also provides three diagnostic diagrams (log-cumulant, kurtosis-skewness, and coefficient-of-variation) with bootstrap concentration ellipses, in the spirit of moment-ratio diagrams. Methods are described in Santos, Ospina, Espinheira and Oliveira (2025).

Authors:Raydonal Ospina [aut, cre]

logcumulant_0.1.0.tar.gz
logcumulant_0.1.0.zip(r-4.7-x86_64)logcumulant_0.1.0.zip(r-4.7-arm64)logcumulant_0.1.0.zip(r-4.6-x86_64)logcumulant_0.1.0.zip(r-4.6-arm64)logcumulant_0.1.0.zip(r-4.5-x86_64)
logcumulant_0.1.0.tgz(r-4.6-x86_64)logcumulant_0.1.0.tgz(r-4.6-arm64)logcumulant_0.1.0.tgz(r-4.5-x86_64)logcumulant_0.1.0.tgz(r-4.5-arm64)
logcumulant_0.1.0.tar.gz(r-4.7-arm64)logcumulant_0.1.0.tar.gz(r-4.7-x86_64)logcumulant_0.1.0.tar.gz(r-4.6-arm64)logcumulant_0.1.0.tar.gz(r-4.6-x86_64)
logcumulant_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
logcumulant/json (API)

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

Bug tracker:https://github.com/raydonal/logcumulant/issues

Pkgdown/docs site:https://raydonal.github.io

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

On CRAN:

Conda:

openblascpp

4.60 score 165 downloads 22 exports 26 dependencies

Last updated from:9a737ea4c2. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK194
source / vignettesOK203
linux-release-arm64OK135
linux-release-x86_64OK160
macos-release-arm64OK107
macos-release-x86_64OK284
macos-oldrel-arm64OK104
macos-oldrel-x86_64OK171
windows-devel-arm64OK257
windows-devel-x86_64OK178
windows-release-arm64OK206
windows-release-x86_64OK148
windows-oldrel-x86_64OK133
wasm-releaseOK120

Exports:ad_cvm_testaic_valuecv_diagramfisher_closedgof_analyzegof_compare_alljacobian_Jkurtosis_diagramldistlog_cumulant_diagrammle_fitmulti_lc_diagrampdistplot_lcpower_studyrdistsize_studyT2_allT2_bootstrapT2_onetheoretical_lcthree_diagrams

Dependencies:actuarclicpp11expintfarverggplot2gluegoftestgridExtragtableisobandlabelinglifecycleMASSnumDerivR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsVGAMviridisLitewithr

Getting started with logcumulant
Why log-cumulants? | A first analysis | Comparing candidate models | Where to go next
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-06-06
Started: 2026-06-06

Goodness-of-fit tests and the bootstrap
The three nested statistics | Why the bootstrap? | Full model comparison
Rendered fromgof-tests.Rmdusingknitr::rmarkdown

Last update: 2026-06-06
Started: 2026-06-06

Simulation studies
Empirical size | Empirical power | Reproducing the figures
Rendered fromsimulation.Rmdusingknitr::rmarkdown

Last update: 2026-06-06
Started: 2026-06-06

The three diagnostic diagrams
Log-cumulant diagram | Kurtosis-skewness diagram | Coefficient-of-variation diagram | All three at once | Several datasets on one diagram
Rendered fromdiagrams.Rmdusingknitr::rmarkdown

Last update: 2026-06-06
Started: 2026-06-06