Package: evinf 0.8.10

evinf: Inference with Extreme Value Inflated Count Data

Allows users to model and draw inferences from extreme value inflated count data, and to evaluate these models and compare to non extreme-value inflated counterparts. The package is built to be compatible with standard presentation tools such as 'broom', 'tidy', and 'modelsummary'.

Authors:David Randahl [cre, aut], Johan Vegelius [aut]

evinf_0.8.10.tar.gz
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evinf_0.8.10.tgz(r-4.4-x86_64)evinf_0.8.10.tgz(r-4.4-arm64)evinf_0.8.10.tgz(r-4.3-x86_64)evinf_0.8.10.tgz(r-4.3-arm64)
evinf_0.8.10.tar.gz(r-4.5-noble)evinf_0.8.10.tar.gz(r-4.4-noble)
evinf_0.8.10.tgz(r-4.4-emscripten)evinf_0.8.10.tgz(r-4.3-emscripten)
evinf.pdf |evinf.html
evinf/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/doktorandahl/evinf/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • genevzinb - Simulated data from the EVZBINB distribution
  • genevzinb2 - Simulated data from the EVZBINB distribution
  • gm_evzinb - A goodness-of-fit gof tibble for GOF metrics when using modelsummary
  • hks - Replication data for Hultman, Kathman, and Shannon (2013) United Nations Peacekeeping and Civilian Protection in Civil War

On CRAN:

8 exports 1.18 score 48 dependencies 248 downloads

Last updated 4 months agofrom:739aca6489. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-win-x86_64OKSep 13 2024
R-4.5-linux-x86_64OKSep 13 2024
R-4.4-win-x86_64OKSep 13 2024
R-4.4-mac-x86_64OKSep 13 2024
R-4.4-mac-aarch64OKSep 13 2024
R-4.3-win-x86_64OKSep 13 2024
R-4.3-mac-x86_64OKSep 13 2024
R-4.3-mac-aarch64OKSep 13 2024

Exports:coefficient_extractorcompare_modelsevinbevzinblr_testoob_evaluationrevinb_fitrevzinb_fit

Dependencies:bbmlebdsmatrixbitopscaToolsclicodetoolscpp11digestdoParalleldoRNGdplyrfansiforeachgenericsgluegplotsgtoolsiteratorsKernSmoothlatticelifecyclemagrittrMASSMatrixmistrMLmetricsmvtnormnumDerivpillarpkgconfigpsclpurrrR6rbibutilsRcppRcppArmadilloRdpackrlangrngtoolsROCRstringistringrtibbletidyrtidyselectutf8vctrswithr

Readme and manuals

Help Manual

Help pageTopics
Bootstrap coefficient extractorcoefficient_extractor
Bootstrap coefficient extractorcoefficient_extractor.evinb
Bootstrap coefficient extractorcoefficient_extractor.evzinb
Bootstrap coefficient extractorcoefficient_extractor.nbboot
Bootstrap coefficient extractorcoefficient_extractor.zinbboot
Function to compare evzinb or evinb models with zinb and nb modelscompare_models
Running an extreme value inflated negative binomial model with bootstrappingevinb
Running an extreme value and zero inflated negative binomial model with bootstrappingevzinb
Simulated data from the EVZBINB distributiongenevzinb
Simulated data from the EVZBINB distributiongenevzinb2
EVZINB and EVINB glance functionsglance.evinb
EVZINB and EVINB glance functionsglance.evzinb
zinbboot and nboot glance functionsglance.nbboot
zinbboot and nboot glance functionsglance.zinbboot
A goodness-of-fit gof tibble for GOF metrics when using modelsummarygm_evzinb
Replication data for Hultman, Kathman, and Shannon (2013) United Nations Peacekeeping and Civilian Protection in Civil Warhks
Likelihood ratio test for individual variables of evzinblr_test
Out of bag predictive performance of EVZINB and EVINB modelsoob_evaluation
Predictions from evinb objectpredict.evinb
Predictions from evzinb objectpredict.evzinb
Prediction for zinbbootpredict.zinbboot
EVINB print functionprint.evinb
EVZINB print functionprint.evzinb
Compare_models print functionprint.evzinbcomp
Random draws from a fitted evinb modelrevinb_fit
Random draws from a fitted evzinb modelrevzinb_fit
EVINB summary functionsummary.evinb
EVZINB summary functionsummary.evzinb
EVINB tidy functiontidy.evinb
EVZINB tidy functiontidy.evzinb
Tidy function for nbboottidy.nbboot
Tidy function for zinbboottidy.zinbboot