The Least-Squares Criteria of the Random Coefficient Dynamic Regression Model

被引:0
|
作者
Autcha Araveeporn
机构
[1] Faculty of Science,Department of Applied Statistics
[2] King Mongkut’s Institute of Technology Ladkrabang,undefined
关键词
62F10; 62F03; Autoregressive; Least-squares criterion; Random coefficient dynamic regression;
D O I
10.1080/15598608.2012.673891
中图分类号
学科分类号
摘要
The random coefficient dynamic regression (RCDR) model develops from random coefficient autoregressive (RCA) model and autoregressive (AR) model. The RCDR model is considered by adding exogenous variables. In this article, the concept of the least-squares (LS) criterion is used to estimate the parameter on the RCDR model. Simulation results have shown that the proposed coefficient of the AR model provided asymptotically unbiased estimates nearly for most of the six data-generating models. The RCDR model is then applied to a series of daily observations of the exchange rate of Baht/GBP and Baht/EUR to illustrate the methodology. The predictions of LS criteria are used with those obtained on 20 hold-out future values of withheld observations.
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页码:315 / 333
页数:18
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