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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:ddbbb812f2. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-linux-x86_64 | OK | Oct 27 2024 |
Exports:checkHistogramdmixnormessHistogramgenIntvmsQuantileparamExamplepmixnormrmixnorm
Dependencies:Rcpp
Readme and manuals
Help Manual
Help page | Topics |
---|---|
The Essential Histogram | essHist-package essHist |
Check any histogram estimator by means of the multiscale confidence set | checkHistogram |
The Essential Histogram | essHistogram |
Generate the system of intervals | genIntv |
The mixture of normal distributions | dmixnorm mixnormal paramExample pmixnorm rmixnorm |
Quantile of the multiscale statistics | msQuantile |