hermiter: Efficient Sequential and Batch Estimation of Probability Density Functions, Cumulative Distribution Functions and Quantiles

Facilitates estimation of the full probability density function, cumulative distribution function and quantile function using Hermite series based estimators. These estimators are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. Based on: Stephanou, Michael, Varughese, Melvin and Iain Macdonald. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245> and Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z>.

Version: 1.0.0
Imports: Rcpp (≥ 1.0.5), methods
LinkingTo: Rcpp, BH
Suggests: testthat, magrittr, knitr, rmarkdown, dplyr, data.table, ggplot2, DT
Published: 2020-09-10
Author: Michael Stephanou [aut, cre], Melvin Varughese [ctb]
Maintainer: Michael Stephanou <michael.stephanou at gmail.com>
BugReports: https://github.com/MikeJaredS/hermiter/issues
License: MIT + file LICENSE
URL: https://github.com/MikeJaredS/hermiter
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: hermiter results

Downloads:

Reference manual: hermiter.pdf
Vignettes: hermiter
Package source: hermiter_1.0.0.tar.gz
Windows binaries: r-devel: hermiter_1.0.0.zip, r-release: hermiter_1.0.0.zip, r-oldrel: hermiter_1.0.0.zip
macOS binaries: r-release: hermiter_1.0.0.tgz, r-oldrel: hermiter_1.0.0.tgz

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