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NNS

Nonlinear Nonparametric Statistics

NNS (Nonlinear Nonparametric Statistics) leverages partial moments – the fundamental elements of variance that asymptotically approximate the area under f(x) – to provide a robust foundation for nonlinear analysis while maintaining linear equivalences. NNS delivers a comprehensive suite of advanced statistical techniques, including: 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).

Versions across snapshots

VersionRepositoryFileSize
12.0 rolling linux/jammy R-4.5 NNS_12.0.tar.gz 1.7 MiB
12.0 rolling linux/noble R-4.5 NNS_12.0.tar.gz 1.7 MiB
12.0 rolling source/ R- NNS_12.0.tar.gz 1.9 MiB
12.0 latest linux/jammy R-4.5 NNS_12.0.tar.gz 1.7 MiB
12.0 latest linux/noble R-4.5 NNS_12.0.tar.gz 1.7 MiB
12.0 latest source/ R- NNS_12.0.tar.gz 1.9 MiB
12.0 2026-04-26 source/ R- NNS_12.0.tar.gz 1.9 MiB
12.0 2026-04-23 source/ R- NNS_12.0.tar.gz 1.9 MiB
11.6.5 2026-04-09 windows/windows R-4.5 NNS_11.6.5.zip 1.9 MiB
11.2 2025-04-20 source/ R- NNS_11.2.tar.gz 1.1 MiB

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