### Abstract

A vector time series model with long-memory dependence is introduced. It is assumed that, at each time point, the observations are equi-correlated. The model is based on a fractionally differenced autoregressive process (long-memory) adjoined to a Gaussian sequence with constant autocorrelation. The maximum likelihood estimators for the parameters in the model are derived and their asymptotic distributions are obtained.

Original language | English (US) |
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Pages (from-to) | 285-293 |

Number of pages | 9 |

Journal | Statistics and Probability Letters |

Volume | 31 |

Issue number | 4 |

State | Published - Feb 1 1997 |

### Fingerprint

### Keywords

- Asymptotic inference
- Long-memory dependence
- Maximum likelihood estimation
- Time series

### ASJC Scopus subject areas

- Statistics and Probability
- Statistics, Probability and Uncertainty

### Cite this

*Statistics and Probability Letters*,

*31*(4), 285-293.

**The asymptotic distribution of the maximum likelihood estimator for a vector time series model with long memory dependence.** / Sethuraman, Sankara N; Basawa, I. V.

Research output: Contribution to journal › Article

*Statistics and Probability Letters*, vol. 31, no. 4, pp. 285-293.

}

TY - JOUR

T1 - The asymptotic distribution of the maximum likelihood estimator for a vector time series model with long memory dependence

AU - Sethuraman, Sankara N

AU - Basawa, I. V.

PY - 1997/2/1

Y1 - 1997/2/1

N2 - A vector time series model with long-memory dependence is introduced. It is assumed that, at each time point, the observations are equi-correlated. The model is based on a fractionally differenced autoregressive process (long-memory) adjoined to a Gaussian sequence with constant autocorrelation. The maximum likelihood estimators for the parameters in the model are derived and their asymptotic distributions are obtained.

AB - A vector time series model with long-memory dependence is introduced. It is assumed that, at each time point, the observations are equi-correlated. The model is based on a fractionally differenced autoregressive process (long-memory) adjoined to a Gaussian sequence with constant autocorrelation. The maximum likelihood estimators for the parameters in the model are derived and their asymptotic distributions are obtained.

KW - Asymptotic inference

KW - Long-memory dependence

KW - Maximum likelihood estimation

KW - Time series

UR - http://www.scopus.com/inward/record.url?scp=0031068130&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031068130&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0031068130

VL - 31

SP - 285

EP - 293

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

IS - 4

ER -