Nonlinear Nonparametric Statistics.

NNS

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

is built on and architecture and is built on with notable performance enhancements.

*Current CRAN version is

Installation

requires . See https://cran.r-project.org/ or for upgrading to latest R release.

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

or via CRAN

install.packages('NNS')

Examples

Please see https://github.com/OVVO-Financial/NNS/blob/NNS-Beta-Version/examples/index.md for basic partial moments equivalences and hands-on statistics, machine learning and econometrics examples.

Citation

@Manual{,
    title = {NNS: Nonlinear Nonparametric Statistics},
    author = {Fred Viole},
    year = {2016},
    note = {R package version 10.7},
    url = {https://CRAN.R-project.org/package=NNS},
  }

Thank you for your interest in NNS!