rexpar-package: rexpar - Robust Methods for Explosive Autoregressive...
In ChrisKust/rexpar: Simplicial Depth for Explosive Autoregressive Processes

Description Details Author(s) References

The package contains simplicial depth statistics for autoregressive processes with explosion (rexpar - robust explosive processes with autoregression). Tests statisticsbased on Kustosz and Mueller (2014), Kustosz, Leucht and Mueller (2016) and Kustosz, Mueller and Wendler (2016) are implemented and some functions to generate examples are included. Further estimators, confidence sets are implementd. For the one dimensional AR Model, we also present a prediction algorithm and change point detection methods for one and two parameter models are proposed, as defined in Kustosz (2016).

Package:	rexpar
Type:	Package
Version:	0.99(1.0beta)
Date:	2014-07-25
License:	GPL-2

Christoph Kustosz and Sebastian Szugat

Maintainer: Kustosz, Christoph <kustosz@statistik.tu-dortmund.de>

Kustosz, C. (2016). Depth based estimators and tests for autoregressive processes with application. Ph. D. thesis. TU Dortmund.

Kustosz C., Leucht A. and Mueller Ch. H. (2016). Tests based on simplicial depth for AR(1) models with explosion. Journal of Time Series Analysis. In press.

Kustosz C., Mueller Ch. H. and Wendler M. (2016). Simplified Simplicial Depth for Regression and Autoregressive Growth Processes. Journal of Statistical Planning and Inference. In press.

Kustosz C. and Mueller Ch. H. (2014). Analysis of crack growth with robust distribution- free estimators and tests for nonstationary autoregressive processes. Statistical Papers 55, 125-140.
Wang X. and Yu, J. (2013). Limit theory for an explosive autoregressive process. Working Paper, No 08-2013. Singapore Management University, School of Economics.