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Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences.

NNS offers: - Numerical Integration & Numerical Differentiation - Partitional & Hierarchial Clustering - Nonlinear Correlation & Dependence - Causal Analysis - Nonlinear Regression & Classification - ANOVA - Seasonality & Autoregressive Modeling - Normalization - Stochastic Dominance - Advanced Monte Carlo Sampling

Companion R-package and datasets to: #### Viole, F. and Nawrocki, D. (2013) Nonlinear Nonparametric Statistics: Using Partial Moments

For a quantitative finance implementation of NNS, see OVVO Labs

Current Version

NNS is built on data.table and doParallel architecture and NNS is built on Rcpp with notable performance enhancements.

*Current NNS CRAN version is CRAN_Status_Badge


NNS requires minimal R version. See or installr for upgrading to latest R release.

library(remotes); remotes::install_github('OVVO-Financial/NNS', ref = "NNS-Beta-Version")

or via CRAN



Please see for basic partial moments equivalences and hands-on statistics, machine learning and econometrics examples.


    title = {NNS: Nonlinear Nonparametric Statistics},
    author = {Fred Viole},
    year = {2016},
    note = {R package version 10.7},
    url = {},

Thank you for your interest in NNS!

CRAN downloads
CRAN downloads