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On preliminary test and shrinkage estimation in linear models with long memory errors

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On preliminary test and shrinkage estimation in linear models with long memory errors. / Mukherjee, Kanchan.
In: Journal of Statistical Planning and Inference, Vol. 69, No. 2, 15.06.1998, p. 319-328.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Mukherjee, K 1998, 'On preliminary test and shrinkage estimation in linear models with long memory errors', Journal of Statistical Planning and Inference, vol. 69, no. 2, pp. 319-328. https://doi.org/10.1016/S0378-3758(97)00160-2

APA

Mukherjee, K. (1998). On preliminary test and shrinkage estimation in linear models with long memory errors. Journal of Statistical Planning and Inference, 69(2), 319-328. https://doi.org/10.1016/S0378-3758(97)00160-2

Vancouver

Mukherjee K. On preliminary test and shrinkage estimation in linear models with long memory errors. Journal of Statistical Planning and Inference. 1998 Jun 15;69(2):319-328. doi: 10.1016/S0378-3758(97)00160-2

Author

Mukherjee, Kanchan. / On preliminary test and shrinkage estimation in linear models with long memory errors. In: Journal of Statistical Planning and Inference. 1998 ; Vol. 69, No. 2. pp. 319-328.

Bibtex

@article{76301467001346a5b3de257bad2d564c,
title = "On preliminary test and shrinkage estimation in linear models with long memory errors",
abstract = "This paper discusses the problem of estimating a subset of parameters when the complementary subset is possibly redundant, in a linear regression model when the errors are generated from a long-memory process. Such a model arises due to the overmodelling of a situation involving long-memory data. Along with the classical least-squares estimator and restricted least-squares estimator, preliminary test least-squares estimator and shrinkage least-squares estimator are investigated in an asymptotic set-up and their relative performances are studied under contiguous alternatives. The contiguous alternatives under such dependence are fundamentally different from those under the independent errors case. ",
keywords = "Long-memory model, Preliminary test estimation , Shrinkage estimation , Contiguous alternatives",
author = "Kanchan Mukherjee",
year = "1998",
month = jun,
day = "15",
doi = "10.1016/S0378-3758(97)00160-2",
language = "English",
volume = "69",
pages = "319--328",
journal = "Journal of Statistical Planning and Inference",
issn = "0378-3758",
publisher = "Elsevier",
number = "2",

}

RIS

TY - JOUR

T1 - On preliminary test and shrinkage estimation in linear models with long memory errors

AU - Mukherjee, Kanchan

PY - 1998/6/15

Y1 - 1998/6/15

N2 - This paper discusses the problem of estimating a subset of parameters when the complementary subset is possibly redundant, in a linear regression model when the errors are generated from a long-memory process. Such a model arises due to the overmodelling of a situation involving long-memory data. Along with the classical least-squares estimator and restricted least-squares estimator, preliminary test least-squares estimator and shrinkage least-squares estimator are investigated in an asymptotic set-up and their relative performances are studied under contiguous alternatives. The contiguous alternatives under such dependence are fundamentally different from those under the independent errors case.

AB - This paper discusses the problem of estimating a subset of parameters when the complementary subset is possibly redundant, in a linear regression model when the errors are generated from a long-memory process. Such a model arises due to the overmodelling of a situation involving long-memory data. Along with the classical least-squares estimator and restricted least-squares estimator, preliminary test least-squares estimator and shrinkage least-squares estimator are investigated in an asymptotic set-up and their relative performances are studied under contiguous alternatives. The contiguous alternatives under such dependence are fundamentally different from those under the independent errors case.

KW - Long-memory model

KW - Preliminary test estimation

KW - Shrinkage estimation

KW - Contiguous alternatives

U2 - 10.1016/S0378-3758(97)00160-2

DO - 10.1016/S0378-3758(97)00160-2

M3 - Journal article

VL - 69

SP - 319

EP - 328

JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

SN - 0378-3758

IS - 2

ER -