Showing 4 of total 4 results (show query)
matthieustigler
tsDyn:Nonlinear Time Series Models with Regime Switching
Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics is available when the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests can be conducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).
Maintained by Matthieu Stigler. Last updated 5 months ago.
34 stars 10.53 score 684 scripts 3 dependents
f-caeiro
randtests:Testing Randomness in R
Provides several non parametric randomness tests for numeric sequences.
Maintained by Frederico Caeiro. Last updated 11 months ago.
4.15 score 235 scripts 3 dependents
kloke
npsm:Nonparametric Statistical Methods
Accompanies the book "Nonparametric Statistical Methods Using R, 2nd Edition" by Kloke and McKean (2024, ISBN:9780367651350). Includes methods, datasets, and random number generation useful for the study of robust and/or nonparametric statistics. Emphasizes classical nonparametric methods for a variety of designs --- especially one-sample and two-sample problems. Includes methods for general scores, including estimation and testing for the two-sample location problem as well as Hogg's adaptive method.
Maintained by John Kloke. Last updated 10 months ago.
3.47 score 59 scripts
