Statistical test for multivariate geographically weighted regression model using the method of maximum likelihood ratio test

Sri Harini; P. Purhadi; M. Mashuri; S. Sunaryo

Statistical test for multivariate geographically weighted regression model using the method of maximum likelihood ratio test

Sri Harini^*, P. Purhadi, M. Mashuri, S. Sunaryo

^*Corresponding author for this work

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

20 Citations (Scopus)

Abstract

Multivariate Geographically Weighted Regression (MGWR) model is an enhancement of the GWR model with the model parameter estimator that is local to each point or location where the data is collected. In MGWR model the vector error is a random and the distributed normal multivariate with mean zero and variance covariance ∑(u _i,v _i). The hypothesis test of MGWR model is done by comparing the suitability of the parameters coefficient simultaneously and partially from MGWR model. Determination of the statistical test is using the method of Maximum Likelihood Ratio Test (MLRT).

Original language	English
Pages (from-to)	110-115
Number of pages	6
Journal	International Journal of Applied Mathematics and Statistics
Volume	29
Issue number	5
Publication status	Published - 2012

Keywords

MGWR
MLRT
Statistical test
Variance covariance

Cite this

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title = "Statistical test for multivariate geographically weighted regression model using the method of maximum likelihood ratio test",

abstract = "Multivariate Geographically Weighted Regression (MGWR) model is an enhancement of the GWR model with the model parameter estimator that is local to each point or location where the data is collected. In MGWR model the vector error is a random and the distributed normal multivariate with mean zero and variance covariance ∑(u i,v i). The hypothesis test of MGWR model is done by comparing the suitability of the parameters coefficient simultaneously and partially from MGWR model. Determination of the statistical test is using the method of Maximum Likelihood Ratio Test (MLRT).",

keywords = "MGWR, MLRT, Statistical test, Variance covariance",

author = "Sri Harini and P. Purhadi and M. Mashuri and S. Sunaryo",

note = "Funding Information: Acknowledgement This work was supported by KOSEF through RCDAMP, and by BK21 Project of Ministry of Education, Korea.",

year = "2012",

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journal = "International Journal of Applied Mathematics and Statistics",

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T1 - Statistical test for multivariate geographically weighted regression model using the method of maximum likelihood ratio test

AU - Harini, Sri

AU - Purhadi, P.

AU - Mashuri, M.

AU - Sunaryo, S.

N1 - Funding Information: Acknowledgement This work was supported by KOSEF through RCDAMP, and by BK21 Project of Ministry of Education, Korea.

PY - 2012

Y1 - 2012

N2 - Multivariate Geographically Weighted Regression (MGWR) model is an enhancement of the GWR model with the model parameter estimator that is local to each point or location where the data is collected. In MGWR model the vector error is a random and the distributed normal multivariate with mean zero and variance covariance ∑(u i,v i). The hypothesis test of MGWR model is done by comparing the suitability of the parameters coefficient simultaneously and partially from MGWR model. Determination of the statistical test is using the method of Maximum Likelihood Ratio Test (MLRT).

AB - Multivariate Geographically Weighted Regression (MGWR) model is an enhancement of the GWR model with the model parameter estimator that is local to each point or location where the data is collected. In MGWR model the vector error is a random and the distributed normal multivariate with mean zero and variance covariance ∑(u i,v i). The hypothesis test of MGWR model is done by comparing the suitability of the parameters coefficient simultaneously and partially from MGWR model. Determination of the statistical test is using the method of Maximum Likelihood Ratio Test (MLRT).

KW - MGWR

KW - MLRT

KW - Statistical test

KW - Variance covariance

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M3 - Article

AN - SCOPUS:84866752091

SN - 0973-1377

VL - 29

SP - 110

EP - 115

JO - International Journal of Applied Mathematics and Statistics

JF - International Journal of Applied Mathematics and Statistics

IS - 5

ER -

Statistical test for multivariate geographically weighted regression model using the method of maximum likelihood ratio test

Abstract

Keywords

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