NNS (Nonlinear Nonparametric Statistics) leverages partial moments –the fundamentalelementsof variance thatasymptotically approximatethe area under f(x) – to provide a robust foundation for nonlinearanalysis while maintaining linear equivalences.
NNS delivers a comprehensive suite of advanced statisticaltechniques, including: - Numerical Integration & NumericalDifferentiation - Partitional & Hierarchial Clustering - NonlinearCorrelation & Dependence - Causal Analysis - Nonlinear Regression& Classification - ANOVA - Seasonality & Autoregressive Modeling- Normalization - Stochastic Dominance - Advanced Monte CarloSampling
Companion R-package and datasets to: #### Viole, F. and Nawrocki, D.(2013) “Nonlinear Nonparametric Statistics: Using PartialMoments” (ISBN: 1490523995)
Current
CRANversion is
requires
. See https://cran.r-project.org/ or
for upgrading to latest R release.
library(remotes); remotes::install_github('OVVO-Financial/NNS',ref ="NNS-Beta-Version")or via CRAN
install.packages('NNS')Please seehttps://github.com/OVVO-Financial/NNS/blob/NNS-Beta-Version/examples/index.mdfor basic partial moments equivalences, hands-on statistics, machinelearning and econometrics examples.
@Manual{, title = {NNS: Nonlinear Nonparametric Statistics}, author = {Fred Viole}, year = {2016}, note = {R package version 11.6.3}, url = {https://CRAN.R-project.org/package=NNS}, }