Bayes unbiased estimators of parameters of linear trend with autoregressive errors

Štulajter, František. "Bayes unbiased estimators of parameters of linear trend with autoregressive errors." Aplikace matematiky 32.6 (1987): 451-458. <http://eudml.org/doc/15515>.

@article{Štulajter1987,
abstract = {The method of least wquares is usually used in a linear regression model $\mathbf \{Y=X\beta +\epsilon \}$ for estimating unknown parameters $\mathbf \{\beta \}$. The case when $\epsilon $ is an autoregressive process of the first order and the matrix $\mathbf \{X\}$ corresponds to a linear trend is studied and the Bayes approach is used for estimating the parameters $\mathbf \{\beta \}$. 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.},
author = {Štulajter, František},
journal = {Aplikace matematiky},
keywords = {autoregressive process of first order; linear trend; Unbiased Bayes estimators; locally best unbiased; least squares estimators; autoregressive process of first order; linear trend; Unbiased Bayes estimators; locally best unbiased; least squares estimators},
language = {eng},
number = {6},
pages = {451-458},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Bayes unbiased estimators of parameters of linear trend with autoregressive errors},
url = {http://eudml.org/doc/15515},
volume = {32},
year = {1987},
}

TY - JOUR
AU - Štulajter, František
TI - Bayes unbiased estimators of parameters of linear trend with autoregressive errors
JO - Aplikace matematiky
PY - 1987
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 32
IS - 6
SP - 451
EP - 458
AB - The method of least wquares is usually used in a linear regression model $\mathbf {Y=X\beta +\epsilon }$ for estimating unknown parameters $\mathbf {\beta }$. The case when $\epsilon $ is an autoregressive process of the first order and the matrix $\mathbf {X}$ corresponds to a linear trend is studied and the Bayes approach is used for estimating the parameters $\mathbf {\beta }$. 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.
LA - eng
KW - autoregressive process of first order; linear trend; Unbiased Bayes estimators; locally best unbiased; least squares estimators; autoregressive process of first order; linear trend; Unbiased Bayes estimators; locally best unbiased; least squares estimators
UR - http://eudml.org/doc/15515
ER -