Tests Based on Simplicial Depth for AR(1) Models With Explosion

Autor:	Christoph P. Kustosz, Christine H. Müller, Anne Leucht
Rok vydání:	2016
Předmět:	Statistics and Probability Explosive material Applied Mathematics 05 social sciences Asymptotic distribution 01 natural sciences 010104 statistics & probability symbols.namesake Autoregressive model Consistency (statistics) Robustness (computer science) 0502 economics and business Outlier Test statistic symbols Applied mathematics 0101 mathematics Statistics Probability and Uncertainty Gaussian process 050205 econometrics Mathematics
Zdroj:	Journal of Time Series Analysis. 37:763-784
ISSN:	0143-9782
Popis:	We propose outlier a robust and distribution‐free test for the explosive AR(1) model with intercept based on simplicial depth. In this model, simplicial depth reduces to counting the cases where three residuals have alternating signs. The asymptotic distribution of the test statistic is given by a specific Gaussian process. Conditions for the consistency are given, and the power of the test at finite samples is compared with alternative tests. The new test outperforms these tests in the case of skewed errors and outliers. Finally, we apply the method to crack growth data and compare the results with an OLS approach.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::19dcfd5a11472a41087f5c7d59ea41fe https://doi.org/10.1111/jtsa.12186 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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