Bayes unbiased estimators of parameters of linear trend with autoregressive errors
Štulajter, František
Applications of Mathematics, Tome 32 (1987), p. 451-458 / Harvested from Czech Digital Mathematics Library
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The method of least wquares is usually used in a linear regression model $\bold {Y=X\beta+\epsilon}$ for estimating unknown parameters $\bold \beta$. The case when $\epsilon$ is an autoregressive process of the first order and the matrix $\bold X$ corresponds to a linear trend is studied and the Bayes approach is used for estimating the parameters $\bold \beta$. Unbiased Bayes estimators are derived for the case of a small number of observations. These estimators are compared with the locally best unbiased ones and with the usual least squares estimators.

Publié le : 1987-01-01
Classification:  62F10,  62F15,  62J05,  62M10 
@article{104276,
     author = {Franti\v sek \v Stulajter},
     title = {Bayes unbiased estimators of parameters of linear trend with autoregressive errors},
     journal = {Applications of Mathematics},
     volume = {32},
     year = {1987},
     pages = {451-458},
     zbl = {0632.62091},
     mrnumber = {0916061},
     language = {en},
     url = {http://dml.mathdoc.fr/item/104276}
}

Štulajter, František. Bayes unbiased estimators of parameters of linear trend with autoregressive errors. Applications of Mathematics, Tome 32 (1987) pp. 451-458. http://gdmltest.u-ga.fr/item/104276/

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