Package: hermiter
Title: Efficient Sequential and Batch Estimation of Univariate and
        Bivariate Probability Density Functions and Cumulative
        Distribution Functions along with Quantiles (Univariate) and
        Spearman's Correlation (Bivariate)
Version: 2.0.3
Authors@R: c(
  person("Michael","Stephanou",role=c("aut","cre"), email="michael.stephanou@gmail.com"),
  person("Melvin","Varughese",role="ctb"))
Author: Michael Stephanou [aut, cre],
  Melvin Varughese [ctb]
Maintainer: Michael Stephanou <michael.stephanou@gmail.com>
Description: Facilitates estimation of full univariate and bivariate 
  probability density functions and cumulative distribution functions along with
  full quantile functions (univariate) and Spearman's rank correlation 
  (bivariate) 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 Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>, 
  Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z> and Stephanou, Michael and Varughese, Melvin. "Sequential Estimation of Nonparametric Correlation using Hermite Series Estimators." arXiv Preprint (2020) <arXiv:2012.06287>.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.5), methods
LinkingTo: Rcpp, BH
RoxygenNote: 7.1.1
Suggests: testthat, magrittr, knitr, rmarkdown, dplyr, data.table,
        ggplot2, DT, mvtnorm, patchwork
VignetteBuilder: knitr
ByteCompile: true
URL: https://github.com/MikeJaredS/hermiter
BugReports: https://github.com/MikeJaredS/hermiter/issues
NeedsCompilation: yes
Packaged: 2021-02-16 13:34:23 UTC; mjste
Repository: CRAN
Date/Publication: 2021-02-17 09:00:20 UTC
