Nonlinear Nonparametric Statistics
Overview
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. Designed for real-world data that violates symmetry, linearity, or distributional assumptions, 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 superiority / dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995, Second edition: https://ovvo-financial.github.io/NNS/book/).
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK12 OK2026-04-25
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- NOTE11 OK, 3 NOTE2026-04-22
- ERROR10 OK, 3 NOTE, 1 ERROR2026-04-18
- NOTE11 OK, 3 NOTE2026-03-10
Documentation
- Help pages
- 49 (2 internal)includes a package overview page
- Examples that run
- 22%10 run in a plain check · 35 never run
- Exported functions with examples
- 96%
- Documented parameters
- 98%
- Return-value docs
- 100%
- Help pages citing references
- 78%
- 01. Getting Started with NNS: Overview
- 02. Getting Started with NNS: Partial Moments
- 03. Getting Started with NNS: Correlation and Dependence
- 04. Getting Started with NNS: Normalization and Rescaling
- 05. Getting Started with NNS: Sampling and Simulation
- 06. Getting Started with NNS: Comparing Distributions
- 07. Getting Started with NNS: Clustering and Regression
- 08. Getting Started with NNS: Classification
- 09. Getting Started with NNS: Forecasting
Downloads
Repository
- PRs merged (all time)
- 98%
- Median days to close, 50 most recently updated closed issues
- 22
- Median days to close, 50 most recently updated closed PRs
- 0
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Checks run against github.com/ovvo-financial/nns on 2026-10-11.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2026-08-11 · The repository has a site deploy workflow
This repository shows signs of AI coding tools.
- Codexfirst seen 2026-03-15Pull request it wrote: opened by a project member
- Claude Codefirst seen 2026-06-13Pull request it wrote: opened by a project memberCommits: 41 by its own account · at least 39 crediting it in the message
- Claude Opus 4.814 commits · Jul 2026
- Claude Fable 513 commits · Jul 2026
- Claude Opus 51 commit · Aug 2026
Dependencies
Installing NNS adds 2 packages (2 with compiled code, 2.5 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppParallel 744 KB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- 13.2Latest
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NNS.SD.Efficient.Setadded 4 exports
LPM.ratio, NNS.SD.efficient.set, PM.matrix, UPM.ratio - 0.3.42017-06-27 · diff ↗
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Co.PM.cor, FSD, TSD, Uni.caus, partition.mapadded 4 exports
NNS.FSD.uni, NNS.TSD.uni, NNS.cor.hd, NNS.part - 0.2.52017-01-11 · diff ↗ ·
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VN.ANOVA, VN.ANOVA.bin, VN.ARMA, VN.FSD, VN.SD.Efficient.Set, VN.SSD, VN.SSD.uni, VN.TSD, VN.caus, VN.cor, VN.dep, VN.norm, VN.reg, VN.seas, findInterval2added 15 exports
NNS.ANOVA, NNS.ANOVA.bin, NNS.ARMA, NNS.FSD, NNS.SD.Efficient.Set, NNS.SSD, NNS.SSD.uni, NNS.TSD, NNS.caus, NNS.cor, NNS.dep, NNS.norm, NNS.reg, NNS.seas, NNS.stack - 0.2.4
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Finite.step, NNS.FWL, NNS.diff, dy.dx - 0.1.9.42016-07-30 · diff ↗
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Co_LPM, Co_UPM, D_LPM, D_UPMadded 12 exports
Co.LPM, Co.UPM, D.LPM, D.UPM, FSD, SSD, TSD, VN.FSD, VN.SD.Efficient.Set, VN.SSD, VN.TSD, VN.dep.reg - 0.1.12016-04-06 · diff ↗ ·
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Co_LPM, Co_UPM, D_LPM, D_UPM, LPM, LPM.VaR, UPM, UPM.VaR, Uni.caus, VN.ANOVA, VN.ANOVA.bin, VN.ARMA, VN.ARMA.reg, VN.caus, VN.cor, VN.dep, VN.norm, VN.reg, VN.seas, partition.map - 0.12016-04-05
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2016-04-05
- Total releases
- 122 / 10 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.6.0
- Download size
- 2.0 MB
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