Testing for normality with applications

This paper considers the problem of testing for normality of the marginal law of univariate and multivariate stationary and weakly dependent random processes using a bootstrap-based Anderson-Darling test statistic. The finite-sample properties of the test are assessed via Monte Carlo experiments. An application to the inflation forecast errors is also presented.

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Year of publication:	2015-03
Authors:	Vavra, Marian
Institutions:	Národná Banka Slovenska
Subject:	testing for normality \| Anderson-Darling statistic \| sieve bootstrap \| weak dependence

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Extent:	application/pdf
Series:	Working and Discussion Papers. - ISSN 1337-5830.
Type of publication:	Book / Working Paper
Notes:	Number WP 1/2015 20 pages
Classification:	C12 - Hypothesis Testing ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C32 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011220341