Bayes Procedures for the Classification of Multiple Polynomial Trends with Dependent Residuals

Autor:	Potter C. Chang, Ben L. Browdy
Rok vydání:	1982
Předmět:	Statistics and Probability Polynomial regression Polynomial Multivariate statistics Relation (database) law.invention Bayes' theorem Invertible matrix law Statistics Applied mathematics Arma process Statistics Probability and Uncertainty Mathematics
Zdroj:	Journal of the American Statistical Association. 77:483-487
ISSN:	1537-274X 0162-1459
DOI:	10.1080/01621459.1982.10477836
Popis:	Three procedures for the classification of multivariate time-dependent data are examined. Two are shown to be Bayes procedures assuming that the time dependence of the data can be described by polynomial regression functions and that the relation among successive residuals is described by a stationary and invertible ARMA process. Relative advantages of these procedures in practical applications and limitations of the model are discussed.
Databáze:	OpenAIRE
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