Prais-Winsten algorithm for regression with second or higher order autoregressive errors

Dimitrios V. Vougas

There is no available Prais-Winsten algorithm for regression with AR(2) or higher order errors, and the one with AR(1) errors is not fully justified or is implemented incorrectly (thus being inefficient). This paper addresses both issues, providing an accurate, computationally fast, and inexpensive generic zig-zag algorithm.

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Year of publication:	2021
Authors:	Vougas, Dimitrios V.
Published in:	Econometrics : open access journal. - Basel : MDPI, ISSN 2225-1146, ZDB-ID 2717594-7. - Vol. 9.2021, 3, Art.-No. 32, p. 1-6
Subject:	autoregressive errors \| exact NLS \| fast zig-zag algorithm \| linear regression \| Prais-Winsten algorithm \| unconditional ML \| Regressionsanalyse \| Regression analysis \| Algorithmus \| Algorithm \| Schätztheorie \| Estimation theory \| Statistischer Fehler \| Statistical error \| Mathematische Optimierung \| Mathematical programming

Type of publication:	Article
Type of publication (narrower categories):	Aufsatz in Zeitschrift ; Article in journal
Language:	English
Other identifiers:	10.3390/econometrics9030032 [DOI] hdl:10419/247622 [Handle]
Source:	ECONIS - Online Catalogue of the ZBW

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