Package: bootGOF 0.1.0.9000

bootGOF: Bootstrap Based Goodness-of-Fit Tests

Bootstrap based goodness-of-fit tests. It allows to perform rigorous statistical tests to check if a chosen model family is correct based on the marked empirical process. The implemented algorithms are described in (Dikta and Scheer (2021) <doi:10.1007/978-3-030-73480-0>) and can be applied to generalized linear models without any further implementation effort. As far as certain linearity conditions are fulfilled the resampling scheme are also applicable beyond generalized linear models. This is reflected in the software architecture which allows to reuse the resampling scheme by implementing only certain interfaces for models that are not supported natively by the package.

Authors:Marsel Scheer [aut, cre], Gerhard Dikta [aut]

bootGOF_0.1.0.9000.tar.gz
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bootGOF.pdf |bootGOF.html
bootGOF/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/marselscheer/bootgof/issues

On CRAN:

4.30 score 2 stars 6 scripts 155 downloads 16 exports 3 dependencies

Last updated 3 years agofrom:d5f97160ac. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winWARNINGOct 27 2024
R-4.5-linuxWARNINGOct 27 2024
R-4.4-winWARNINGOct 27 2024
R-4.4-macWARNINGOct 27 2024
R-4.3-winWARNINGOct 27 2024
R-4.3-macWARNINGOct 27 2024

Exports:GOF_glm_info_extractorGOF_glm_sim_paramGOF_glm_trainerGOF_lm_info_extractorGOF_lm_sim_paramGOF_lm_trainerGOF_modelGOF_model_info_extractorGOF_model_resampleGOF_model_simulatorGOF_model_testGOF_model_trainerGOF_sim_wild_rademacherRn1_CvMRn1_KSRn1_statistic

Dependencies:backportscheckmateR6

Architecture

Rendered fromArchitecture.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2021-01-18
Started: 2021-01-18

New-Models

Rendered fromNew-Models.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2021-01-18
Started: 2021-01-18