Best linear unbiased prediction in the two-way error components model with AR(1) error processes

被引：0

作者：

Kelik, Serge Tayim ^{[1
]}

Soh, Patrice Takam ^{[1
]}

Kouassi, Eugene ^{[2
]}

Fotso, Simeon ^{[3
]}

机构：

[1] Univ Yaounde I, Dept Math, Yaounde, Cameroon

[2] Univ Montreal, Dept Econ, Montreal, PQ, Canada

[3] Univ Yaounde I, Higher Teacher Training Coll, Dept Math, Yaounde, Cameroon

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2025年

关键词：

BLUP; Data and regression results; Extensions; Gain in efficiency; Prediction functions; Two-way error components model; CROSS-SECTION; SUFFICIENCY; ESTIMATORS; INVERSE;

D O I：

10.1080/03610918.2025.2519508

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, the derivation of the Best Linear Unbiased Predictor (BLUP) in the context of the two-way error components model is obtained under fairly general conditions. Then the prediction functions, parameter estimations as well as the gains in efficiency are subsequently derived. The results obtained are extended taking into account autoregressive processes of order 1 (AR(1)) in the error terms. Some Monte Carlo experiments conducted indicate that the model performs reasonably well for some suitable values of N and T.

引用

页数：23