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.
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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')) |
Bug tracker:https://github.com/marselscheer/bootgof/issues
Last updated 3 years agofrom:d5f97160ac. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
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Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-win | WARNING | Oct 27 2024 |
R-4.5-linux | WARNING | Oct 27 2024 |
R-4.4-win | WARNING | Oct 27 2024 |
R-4.4-mac | WARNING | Oct 27 2024 |
R-4.3-win | WARNING | Oct 27 2024 |
R-4.3-mac | WARNING | Oct 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
Readme and manuals
Help Manual
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