### 抄録

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.

元の言語 | English |
---|---|

ページ（範囲） | 3213-3224 |

ページ数 | 12 |

ジャーナル | Communications in Statistics - Theory and Methods |

巻 | 38 |

発行部数 | 16-17 |

DOI | |

出版物ステータス | Published - 2009 1 |

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### ASJC Scopus subject areas

- Statistics and Probability

### これを引用

*Communications in Statistics - Theory and Methods*,

*38*(16-17), 3213-3224. https://doi.org/10.1080/03610920902947741

**Preliminary test estimation for regression models with long-memory disturbance.** / Taniguchi, Masanobu; Ogata, Hiroaki; Shiraishi, Hiroshi.

研究成果: Article

*Communications in Statistics - Theory and Methods*, 巻. 38, 番号 16-17, pp. 3213-3224. https://doi.org/10.1080/03610920902947741

}

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

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 -