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Nonlinear Nonparametric Statistics
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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
  • Seasonality & Autoregressive Modeling
  • Normalization
  • Stochastic Dominance

Companion R-package and datasets to:

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments"

Current Version

NNS is built on doParallel architecture with notable performance enhancements.

NNS is built on data.table architecture 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.

require(devtools); 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 0.4.9},
    url = {},

Thank you for your interest in NNS!

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