Package: essHist 1.2.2

Housen Li

essHist: The Essential Histogram

Provide an optimal histogram, in the sense of probability density estimation and features detection, by means of multiscale variational inference. In other words, the resulting histogram servers as an optimal density estimator, and meanwhile recovers the features, such as increases or modes, with both false positive and false negative controls. Moreover, it provides a parsimonious representation in terms of the number of blocks, which simplifies data interpretation. The only assumption for the method is that data points are independent and identically distributed, so it applies to fairly general situations, including continuous distributions, discrete distributions, and mixtures of both. For details see Li, Munk, Sieling and Walther (2016) <arxiv:1612.07216>.

Authors:Housen Li [aut, cre], Hannes Sieling [aut]

essHist_1.2.2.tar.gz
essHist_1.2.2.tar.gz(r-4.5-noble)essHist_1.2.2.tar.gz(r-4.4-noble)
essHist_1.2.2.tgz(r-4.4-emscripten)essHist_1.2.2.tgz(r-4.3-emscripten)
essHist.pdf |essHist.html
essHist/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

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

1.00 score 1 stars 6 scripts 193 downloads 8 exports 1 dependencies

Last updated 6 years agofrom:ddbbb812f2. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-linux-x86_64OKOct 27 2024

Exports:checkHistogramdmixnormessHistogramgenIntvmsQuantileparamExamplepmixnormrmixnorm

Dependencies:Rcpp