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essHist
View on CRAN: Click
here
Download and install essHist package within the R console
Install from CRAN:
install.packages("essHist")
Install from Github:
library("remotes")
install_github("cran/essHist") Install by package version:
library("remotes")
install_version("essHist", "1.2.2") Attach the package and use:
library("essHist")
Maintained by
Housen Li
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-02-05
Latest Update: 2019-05-10
Description:
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) .
How to cite:
Housen Li (2018). essHist: The Essential Histogram. R package version 1.2.2, https://cran.r-project.org/web/packages/essHist. Accessed 08 Jun. 2026.
Previous versions and publish date:
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Complete documentation for essHist
Functions, R codes and Examples using
the essHist R package
Some associated functions: checkHistogram . essHist-package . essHistogram . genIntv . mixnorm . msQuantile .
Some associated R codes: RcppExports.R . checkHistogram.R . essHistogram.R . intv.R . mixtureDistribution.R . msQuantile.R . Full essHist package functions and examples
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