On Koul's minimum distance estimators in the regression models with long memory moving averages

被引：7

作者：

Li, LY ^{[1
]}

机构：

[1] Univ New Hampshire, Dept Math & Stat, Durham, NH 03824 USA

来源：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2003年 / 105卷 / 02期

关键词：

long-range dependence; multiple linear model; weighted empirical; asymptotic normality; LINEAR-REGRESSION; EMPIRICAL PROCESS; ASYMPTOTIC-EXPANSION; TIME-SERIES; ERRORS;

D O I：

10.1016/S0304-4149(02)00266-1

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper discusses the asymptotic behavior of Koul's minimum distance estimators of the regression parameter vector in linear regression models with long memory moving average errors, when the design variables are known constants. It is observed that all these estimators are asymptotically equivalent to the least-squares estimator in the first order. (C) 2003 Elsevier Science B.V. All rights reserved.

引用

页码：257 / 269

页数：13

共 50 条

[41] Lack of fit test for long memory regression models
Wang, Lihong
STATISTICAL PAPERS, 2020, 61 (03) : 1043 - 1067
[42] Maximum-likelihood estimators and random walks in long memory models
Bertin, Karine
Torres, Soledad
Tudor, Ciprian A.
STATISTICS, 2011, 45 (04) : 361 - 374
[43] ON A CLASS OF M-ESTIMATORS FOR GAUSSIAN LONG-MEMORY MODELS
BERAN, J
BIOMETRIKA, 1994, 81 (04) : 755 - 766
[44] Generalized least squares estimators for covariance parameters for credibility regression models with moving average errors
Cossette, H
Luong, A
INSURANCE MATHEMATICS & ECONOMICS, 2003, 32 (02): : 281 - 293
[45] Asymptotics of M-estimators in non-linear regression with long memory designs
Koul, HL
Baillie, RT
STATISTICS & PROBABILITY LETTERS, 2003, 61 (03) : 237 - 252
[46] Asymptotics of minimum distance estimator in linear regression models under strong-mixing
Yang, Y
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 1998, 27 (07) : 1619 - 1637
[47] Minimum distance quantile regression for spatial autoregressive panel data models with fixed effects
Dai, Xiaowen
Jin, Libin
PLOS ONE, 2021, 16 (12):
[48] Minimum hellinger distance estimation for finite mixtures of Poisson regression models and its applications
Lu, Z
Van Hui, Y
Lee, AH
BIOMETRICS, 2003, 59 (04) : 1016 - 1026
[49] Minimum distance lack-of-fit tests under long memory errors
Hira L. Koul
Donatas Surgailis
Nao Mimoto
Metrika, 2015, 78 : 119 - 143
[50] Memory-type ratio and product estimators for population variance using exponentially weighted moving averages for time-scaled surveys
Qureshi, Muhammad Nouman
Tariq, Muhammad Umair
Hanif, Muhammad
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2024, 53 (03) : 1484 - 1493

← 1 2 3 4 5 →