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
- Partitional & Hierarchial Clustering
- Nonlinear Correlation & Dependence
- Causal Analysis
- Nonlinear Regression & Classification
- ANOVA
- Seasonality & Autoregressive Modeling
- Normalization
- Stochastic Dominance
Companion R-package and datasets to:
Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments"
is built on
architecture with notable performance enhancements.
is built on
architecture with notable performance enhancements.
requires
. See https://cran.r-project.org/ or
for upgrading to latest R release.
require(devtools); install_github('OVVO-Financial/NNS', ref = "NNS-Beta-Version")
or via CRAN
install.packages('NNS')
Please see https://github.com/OVVO-Financial/NNS/blob/NNS-Beta-Version/examples/index.md for basic partial moments equivalences and hands-on statistics, machine learning and econometrics examples.
@Manual{,
title = {NNS: Nonlinear Nonparametric Statistics},
author = {Fred Viole},
year = {2016},
note = {R package version 0.4.4},
url = {https://CRAN.R-project.org/package=NNS},
}