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NNS: Nonlinear Nonparametric Statistics
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, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Getting started
README.md
Getting Started with NNS: Classification'
Getting Started with NNS: Clustering and Regression"
Getting Started with NNS: Comparing Distributions"
Getting Started with NNS: Correlation and Dependence"
Getting Started with NNS: Forecasting"
Getting Started with NNS: Partial Moments"
Getting Started with NNS: Sampling and Simulation"
Browse package contents
Package details |
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| Author | Fred Viole [aut, cre], Roberto Spadim [ctb] |
| Maintainer | Fred Viole <ovvo.financial.systems@gmail.com> |
| License | GPL-3 |
| Version | 10.9.3 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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