Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors

Dong Wan Shin; Dai Gyoung Kim; Han Joon Kim

doi:10.1007/s001840100177

Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors

Dong Wan Shin, Dai Gyoung Kim, Han Joon Kim

Department of Statistics

Research output: Contribution to journal › Article › peer-review

Abstract

For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the generalized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.

Original language	English
Pages (from-to)	247-258
Number of pages	12
Journal	Metrika
Volume	56
Issue number	3
DOIs	https://doi.org/10.1007/s001840100177
State	Published - 2002

Keywords

Efficiency
GLSE
OLSE
Sinusoidal surface
Spatial regression

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10.1007/s001840100177

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title = "Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors",

abstract = "For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the generalized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.",

keywords = "Efficiency, GLSE, OLSE, Sinusoidal surface, Spatial regression",

author = "Shin, {Dong Wan} and Kim, {Dai Gyoung} and Kim, {Han Joon}",

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T1 - Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors

AU - Shin, Dong Wan

AU - Kim, Dai Gyoung

AU - Kim, Han Joon

PY - 2002

Y1 - 2002

N2 - For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the generalized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.

AB - For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the generalized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.

KW - Efficiency

KW - GLSE

KW - OLSE

KW - Sinusoidal surface

KW - Spatial regression

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DO - 10.1007/s001840100177

M3 - Article

AN - SCOPUS:0036459221

SN - 0026-1335

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SP - 247

EP - 258

JO - Metrika

JF - Metrika

IS - 3

ER -

Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors

Abstract

Keywords

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