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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" (ISBN: 1490523995)

For a quantitative finance implementation of NNS, see OVVO Labs

Current Version

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, hands-on statistics, machine learning and econometrics examples.

Citation

@Manual{,
    title = {NNS: Nonlinear Nonparametric Statistics},
    author = {Fred Viole},
    year = {2016},
    note = {R package version 11.1},
    url = {https://CRAN.R-project.org/package=NNS},
  }

Thank you for your interest in NNS!

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Version

Install

install.packages('NNS')

Monthly Downloads

1,325

Version

11.1

License

GPL-3

Maintainer

Fred Viole

Last Published

February 17th, 2025

Functions in NNS (11.1)

NNS.FSD.uni

NNS FSD Test uni-directional
NNS.MC

NNS Monte Carlo Sampling
NNS.SSD

NNS SSD Test
NNS.SD.cluster

NNS SD-based Clustering
NNS.SSD.uni

NNS SSD Test uni-directional
NNS.gravity

NNS gravity
NNS.meboot

NNS meboot
NNS.TSD.uni

NNS TSD Test uni-directional
NNS.FSD

NNS FSD Test
NNS.VAR

NNS VAR
NNS.distance

NNS Distance
NNS.diff

NNS Numerical Differentiation
NNS.boost

NNS Boost
NNS.caus

NNS Causation
NNS.mode

NNS mode
NNS.dep

NNS Dependence
NNS.moments

NNS moments
NNS.part

NNS Partition Map
NNS.stack

NNS Stack
NNS.norm

NNS Normalization
NNS.nowcast

NNS Nowcast
NNS.copula

NNS Co-Partial Moments Higher Dimension Dependence
NNS.seas

NNS Seasonality Test
NNS.rescale

NNS rescale
NNS.reg

NNS Regression
UPM.ratio

Upper Partial Moment RATIO
PM.matrix

Partial Moment Matrix
NNS.term.matrix

NNS Term Matrix
dy.dx

Partial Derivative dy/dx
dy.d_

Partial Derivative dy/d_[wrt]
UPM.VaR

UPM VaR
UPM

Upper Partial Moment
NNS.ANOVA

NNS ANOVA
LPM

Lower Partial Moment
NNS.ARMA

NNS ARMA
Co.LPM

Co-Lower Partial Moment (Lower Left Quadrant 4)
D.UPM

Divergent-Upper Partial Moment (Upper Left Quadrant 2)
LPM.ratio

Lower Partial Moment RATIO
LPM.VaR

LPM VaR
NNS.ARMA.optim

NNS ARMA Optimizer
Co.UPM

Co-Upper Partial Moment (Upper Right Quadrant 1)
D.LPM

Divergent-Lower Partial Moment (Lower Right Quadrant 3)
NNS.CDF

NNS CDF
NNS.TSD

NNS TSD Test
NNS.SD.efficient.set

NNS SD Efficient Set
NNS

NNS: Nonlinear Nonparametric Statistics