COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM

ABSTRACT: The dependency of spatial data can be quantified through semivariogram, which is an important part in estimation processes. In this thesis, a method for constructing semivariogram model using copula formalism is discusse...

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Main Author:	Febrian Umbara (NIM 20105015), Rian
Format:	Theses
Language:	Indonesia
Online Access:	https://digilib.itb.ac.id/gdl/view/6672
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Institution:	Institut Teknologi Bandung
Language:	Indonesia

id	id-itb.:6672
spelling	id-itb.:66722017-09-27T14:41:44ZCOPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM Febrian Umbara (NIM 20105015), Rian Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/6672 ABSTRACT: <br /> <br /> <br /> <br /> <br /> The dependency of spatial data can be quantified through semivariogram, which is an important part in estimation processes. In this thesis, a method for constructing semivariogram model using copula formalism is discussed. The model is constructed based on median regression which is derived from a copula. By using copula formalism, it is no longer necessary to force using any a priori semivariogram models. After the model is obtained, it is used in estimation processes using ordinary kriging and sequential kriging methods. The computational complexity of the sequential kriging method is much lower than that of the ordinary kriging method and the results of those methods are not significantly different. The computational complexity of the sequential kriging can still be reduced so that its algorithm will be more efficient. text
institution	Institut Teknologi Bandung
building	Institut Teknologi Bandung Library
continent	Asia
country	Indonesia Indonesia
content_provider	Institut Teknologi Bandung
collection	Digital ITB
language	Indonesia
description	ABSTRACT: <br /> <br /> <br /> <br /> <br /> The dependency of spatial data can be quantified through semivariogram, which is an important part in estimation processes. In this thesis, a method for constructing semivariogram model using copula formalism is discussed. The model is constructed based on median regression which is derived from a copula. By using copula formalism, it is no longer necessary to force using any a priori semivariogram models. After the model is obtained, it is used in estimation processes using ordinary kriging and sequential kriging methods. The computational complexity of the sequential kriging method is much lower than that of the ordinary kriging method and the results of those methods are not significantly different. The computational complexity of the sequential kriging can still be reduced so that its algorithm will be more efficient.
format	Theses
author	Febrian Umbara (NIM 20105015), Rian
spellingShingle	Febrian Umbara (NIM 20105015), Rian COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM
author_facet	Febrian Umbara (NIM 20105015), Rian
author_sort	Febrian Umbara (NIM 20105015), Rian
title	COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM
title_short	COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM
title_full	COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM
title_fullStr	COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM
title_full_unstemmed	COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM
title_sort	copula-based semivariogram model and computational reduction on the sequential kriging algorithm
url	https://digilib.itb.ac.id/gdl/view/6672
_version_	1820663944991211520

COPULA-BASED SEMIVARIOGRAM MODEL AND COMPUTATIONAL REDUCTION ON THE SEQUENTIAL KRIGING ALGORITHM

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