hermiter: R package for Sequential Nonparametric Estimation

Abstract

This article introduces the R package hermiter which facilitates estimation of univariate and bivariate probability density functions and cumulative distribution functions along with full quantile functions (univariate) and nonparametric correlation coefficients (bivariate) using Hermite series based estimators. The algorithms implemented in the hermiter package are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. In addition, the Hermite series based estimators are approximately mergeable allowing parallel and distributed estimation.

arXiv comment33 pages plus references, 11 figures. Incorporates journal reviewer and editor comments. As appears in Computational Statistics

References in corpus (4)

• DDSketch: A fast and fully-mergeable quantile sketch with relative-error guarantees
• Sequential estimation of Spearman rank correlation using Hermite series estimators
• Sequential Quantiles via Hermite Series Density Estimation
• A Survey of Approximate Quantile Computation on Large-scale Data (Technical Report)