An approximate likelihood function for panel data with a mixed ARMA(p, q) remainder disturbance model
An approximate likelihood function for panel data with an autoregressive moving-average (ARMA)(p, q) model remainder disturbance is presented and Whittle's approximate maximum likelihood estimator (MLE) is used to yield an asymptotic estimator. Although an asymptotic approach, the power test is quite successful for estimating and testing. In this approach, we do not need to calculate the transformation matrix in exact form. Through the Riemann sum approach, we can construct a simple approximate concentrated likelihood function. In addition, the model is also extended to the restricted maximum likelihood (REML) function, in which the package of Gilmour, Thompson and Cullis [Biometrics (1995) Vol. 51, pp. 1440-1450] is applied without difficulty. In the case study, we implement the model on the characteristic line for the investment analysis of Taiwanese computer motherboard makers. Copyright 2006 The Author Journal compilation 2006 Blackwell Publishing Ltd.
Year of publication: |
2006
|
---|---|
Authors: | Chen, Wen-Den |
Published in: |
Journal of Time Series Analysis. - Wiley Blackwell, ISSN 0143-9782. - Vol. 27.2006, 6, p. 911-921
|
Publisher: |
Wiley Blackwell |
Saved in:
Saved in favorites
Similar items by person
-
Estimating the long memory granger causality effect with a spectrum estimator
Chen, Wen-den, (2006)
-
Is it a short-memory, long-memory, or permanently Granger-causation influence?
Chen, Wen-Den, (2008)
-
Chen, Wen-Den, (2008)
- More ...