Package: imprecise101 0.2.2.4

Chel Hee Lee

imprecise101: Introduction to Imprecise Probabilities

An imprecise inference presented in the study of Walley (1996) <doi:10.1111/j.2517-6161.1996.tb02065.x> is one of the statistical reasoning methods when prior information is unavailable. Functions and utils needed for illustrating this inferential paradigm are implemented for classroom teaching and further comprehensive research. Two imprecise models are demonstrated using multinomial data and 2x2 contingency table data. The concepts of prior ignorance and imprecision are discussed in lower and upper probabilities. Representation invariance principle, hypothesis testing, decision-making, and further generalization are also illustrated.

Authors:Chel Hee Lee [aut, cre], Mikelis Bickis [ctb], Angela McCourt [ctb]

imprecise101_0.2.2.4.tar.gz
imprecise101_0.2.2.4.tar.gz(r-4.5-noble)imprecise101_0.2.2.4.tar.gz(r-4.4-noble)
imprecise101_0.2.2.4.tgz(r-4.4-emscripten)imprecise101_0.2.2.4.tgz(r-4.3-emscripten)
imprecise101.pdf |imprecise101.html✨
imprecise101/json (API)

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

6 exports 0.00 score 72 dependencies 2 scripts 177 downloads

Last updated 2 years agofrom:b6f16e9bf4. Checks:OK: 1 NOTE: 1. Indexed: yes.

Exports:dbetabinomdbetadifhpdibmidmpbetabinom

Dependencies:askpassbase64encbslibcachemclicolorspacecpp11crosstalkcurldata.tabledigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplotlypromisespsclpurrrR6rappdirsRColorBrewerRcpprlangrmarkdownsassscalesstringistringrsystibbletidyrtidyselecttinytextoleranceutf8vctrsviridisLitewithrxfunyaml