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
- VignetteGetting Started with NNS: Clustering and Regression
- VignetteGetting Started with NNS: Comparing Distributions
- VignetteGetting Started with NNS: Correlation and Dependence
- VignetteGetting Started with NNS: Forecasting
- VignetteGetting Started with NNS: Partial Moments
- VignetteGetting Started with NNS: Sampling and Simulation
- MaterialREADME
- In ViewsEconometrics
Team
Fred Viole
Roberto Spadim
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- Imports10 packages
- Suggests3 packages
- Linking To2 packages
- Reverse Imports2 packages
- Reverse Suggests1 package