Abstract
For a class of time series regression models with long-memory disturbance, we are interested in estimation of a subset of the regression coefficient vector and spectral parameter of the residual process when the complementary subset is suspected to be close to 0. In this situation, we evaluate the mean square errors of the restricted and unrestricted MLE and a preliminary test estimator when the complementary parameters are contiguous to zero vector. The results are expressed in terms of the regression spectra and the residual spectra. Since we assume long-memory dependence for the disturbance, the asymptotics are much different from the case of i.i.d. disturbance. Numerical studies elucidate some interesting features of regression and long-memory structures.
| Original language | English |
|---|---|
| Pages (from-to) | 3213-3224 |
| Number of pages | 12 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 38 |
| Issue number | 16-17 |
| DOIs | |
| Publication status | Published - 2009 Jan |
| Externally published | Yes |
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Keywords
- Fractional spectral density
- LAN theorem
- Long-memory process
- Preliminary test estimator
- Restricted MLE
- Time regression model
- Unrestricted MLE
ASJC Scopus subject areas
- Statistics and Probability
Cite this
Preliminary test estimation for regression models with long-memory disturbance. / Taniguchi, Masanobu; Ogata, Hiroaki; Shiraishi, Hiroshi.
In: Communications in Statistics - Theory and Methods, Vol. 38, No. 16-17, 01.2009, p. 3213-3224.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Preliminary test estimation for regression models with long-memory disturbance
AU - Taniguchi, Masanobu
AU - Ogata, Hiroaki
AU - Shiraishi, Hiroshi
PY - 2009/1
Y1 - 2009/1
N2 - For a class of time series regression models with long-memory disturbance, we are interested in estimation of a subset of the regression coefficient vector and spectral parameter of the residual process when the complementary subset is suspected to be close to 0. In this situation, we evaluate the mean square errors of the restricted and unrestricted MLE and a preliminary test estimator when the complementary parameters are contiguous to zero vector. The results are expressed in terms of the regression spectra and the residual spectra. Since we assume long-memory dependence for the disturbance, the asymptotics are much different from the case of i.i.d. disturbance. Numerical studies elucidate some interesting features of regression and long-memory structures.
AB - For a class of time series regression models with long-memory disturbance, we are interested in estimation of a subset of the regression coefficient vector and spectral parameter of the residual process when the complementary subset is suspected to be close to 0. In this situation, we evaluate the mean square errors of the restricted and unrestricted MLE and a preliminary test estimator when the complementary parameters are contiguous to zero vector. The results are expressed in terms of the regression spectra and the residual spectra. Since we assume long-memory dependence for the disturbance, the asymptotics are much different from the case of i.i.d. disturbance. Numerical studies elucidate some interesting features of regression and long-memory structures.
KW - Fractional spectral density
KW - LAN theorem
KW - Long-memory process
KW - Preliminary test estimator
KW - Restricted MLE
KW - Time regression model
KW - Unrestricted MLE
UR - http://www.scopus.com/inward/record.url?scp=70249143971&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70249143971&partnerID=8YFLogxK
U2 - 10.1080/03610920902947741
DO - 10.1080/03610920902947741
M3 - Article
AN - SCOPUS:70249143971
VL - 38
SP - 3213
EP - 3224
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
SN - 0361-0926
IS - 16-17
ER -