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)

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 , Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) and Stephanou, Michael and Varughese, Melvin. "Sequential Estimation of Nonparametric Correlation using Hermite Series Estimators." arXiv Preprint (2020) .


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install.packages("hermiter")

2.0.3 by Michael Stephanou, 13 days ago


https://github.com/MikeJaredS/hermiter


Report a bug at https://github.com/MikeJaredS/hermiter/issues


Browse source code at https://github.com/cran/hermiter


Authors: Michael Stephanou [aut, cre] , Melvin Varughese [ctb]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, methods

Suggests testthat, magrittr, knitr, rmarkdown, dplyr, data.table, ggplot2, DT, mvtnorm, patchwork

Linking to Rcpp, BH


See at CRAN