Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression

We establish an asymptotic approach for checking the appropriateness of an assumed multivariate spatial regression model by considering the set-indexed partial sums process of the least squares residuals of the vector of observations. In this work, we assume that the components of the observation, w...

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Main Authors: Wayan Somayasa, Gusti N. Adhi Wibawa, La Hamimu, La Ode Ngkoimani
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:International Journal of Mathematics and Mathematical Sciences
Online Access:http://dx.doi.org/10.1155/2016/2601601
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author Wayan Somayasa
Gusti N. Adhi Wibawa
La Hamimu
La Ode Ngkoimani
author_facet Wayan Somayasa
Gusti N. Adhi Wibawa
La Hamimu
La Ode Ngkoimani
author_sort Wayan Somayasa
collection DOAJ
description We establish an asymptotic approach for checking the appropriateness of an assumed multivariate spatial regression model by considering the set-indexed partial sums process of the least squares residuals of the vector of observations. In this work, we assume that the components of the observation, whose mean is generated by a certain basis, are correlated. By this reason we need more effort in deriving the results. To get the limit process we apply the multivariate analog of the well-known Prohorov’s theorem. To test the hypothesis we define tests which are given by Kolmogorov-Smirnov (KS) and Cramér-von Mises (CvM) functionals of the partial sums processes. The calibration of the probability distribution of the tests is conducted by proposing bootstrap resampling technique based on the residuals. We studied the finite sample size performance of the KS and CvM tests by simulation. The application of the proposed test procedure to real data is also discussed.
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spelling doaj-art-c41cfca875f94e57b469b7162ddb40472025-08-20T02:18:57ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252016-01-01201610.1155/2016/26016012601601Asymptotic Theory in Model Diagnostic for General Multivariate Spatial RegressionWayan Somayasa0Gusti N. Adhi Wibawa1La Hamimu2La Ode Ngkoimani3Department of Mathematics, Haluoleo University, Kendari, IndonesiaDepartment of Mathematics, Haluoleo University, Kendari, IndonesiaDepartment of Geological Engineering, Haluoleo University, Kendari, IndonesiaDepartment of Geological Engineering, Haluoleo University, Kendari, IndonesiaWe establish an asymptotic approach for checking the appropriateness of an assumed multivariate spatial regression model by considering the set-indexed partial sums process of the least squares residuals of the vector of observations. In this work, we assume that the components of the observation, whose mean is generated by a certain basis, are correlated. By this reason we need more effort in deriving the results. To get the limit process we apply the multivariate analog of the well-known Prohorov’s theorem. To test the hypothesis we define tests which are given by Kolmogorov-Smirnov (KS) and Cramér-von Mises (CvM) functionals of the partial sums processes. The calibration of the probability distribution of the tests is conducted by proposing bootstrap resampling technique based on the residuals. We studied the finite sample size performance of the KS and CvM tests by simulation. The application of the proposed test procedure to real data is also discussed.http://dx.doi.org/10.1155/2016/2601601
spellingShingle Wayan Somayasa
Gusti N. Adhi Wibawa
La Hamimu
La Ode Ngkoimani
Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression
International Journal of Mathematics and Mathematical Sciences
title Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression
title_full Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression
title_fullStr Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression
title_full_unstemmed Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression
title_short Asymptotic Theory in Model Diagnostic for General Multivariate Spatial Regression
title_sort asymptotic theory in model diagnostic for general multivariate spatial regression
url http://dx.doi.org/10.1155/2016/2601601
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AT gustinadhiwibawa asymptotictheoryinmodeldiagnosticforgeneralmultivariatespatialregression
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AT laodengkoimani asymptotictheoryinmodeldiagnosticforgeneralmultivariatespatialregression