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).
- Version10.9.3
- R version≥ 3.6.0
- LicenseGPL-3
- Needs compilation?Yes
- Last release10/14/2024
Documentation
- VignetteGetting Started with NNS: Classification
- Vignettesource
- VignetteR code
- VignetteGetting Started with NNS: Clustering and Regression
- Vignettesource
- VignetteR code
- VignetteGetting Started with NNS: Comparing Distributions
- Vignettesource
- VignetteR code
- VignetteGetting Started with NNS: Correlation and Dependence
- Vignettesource
- VignetteR code
- VignetteGetting Started with NNS: Forecasting
- Vignettesource
- VignetteR code
- VignetteGetting Started with NNS: Partial Moments
- Vignettesource
- VignetteR code
- VignetteGetting Started with NNS: Sampling and Simulation
- Vignettesource
- VignetteR code
- MaterialREADME
- In ViewsEconometrics
Team
Fred Viole
Roberto Spadim
Show author detailsRolesContributor
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- Depends1 package
- Imports10 packages
- Suggests3 packages
- Linking To2 packages
- Reverse Imports2 packages
- Reverse Suggests1 package