Jack knifing for semivariogram validation

Detalhes bibliográficos
Autor(a) principal: Vieira,Sidney Rosa
Data de Publicação: 2010
Outros Autores: Carvalho,José Ruy Porto de, González,Antonio Paz
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bragantia
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500011
Resumo: The semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to choose a better fit in distinct regions of the semivariogram.
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spelling Jack knifing for semivariogram validationSemivariogramsstationaritytopographyscale of variationThe semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to choose a better fit in distinct regions of the semivariogram.Instituto Agronômico de Campinas2010-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500011Bragantia v.69 suppl.0 2010reponame:Bragantiainstname:Instituto Agronômico de Campinas (IAC)instacron:IAC10.1590/S0006-87052010000500011info:eu-repo/semantics/openAccessVieira,Sidney RosaCarvalho,José Ruy Porto deGonzález,Antonio Pazeng2011-02-14T00:00:00Zoai:scielo:S0006-87052010000500011Revistahttps://www.scielo.br/j/brag/https://old.scielo.br/oai/scielo-oai.phpbragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br1678-44990006-8705opendoar:2011-02-14T00:00Bragantia - Instituto Agronômico de Campinas (IAC)false
dc.title.none.fl_str_mv Jack knifing for semivariogram validation
title Jack knifing for semivariogram validation
spellingShingle Jack knifing for semivariogram validation
Vieira,Sidney Rosa
Semivariograms
stationarity
topography
scale of variation
title_short Jack knifing for semivariogram validation
title_full Jack knifing for semivariogram validation
title_fullStr Jack knifing for semivariogram validation
title_full_unstemmed Jack knifing for semivariogram validation
title_sort Jack knifing for semivariogram validation
author Vieira,Sidney Rosa
author_facet Vieira,Sidney Rosa
Carvalho,José Ruy Porto de
González,Antonio Paz
author_role author
author2 Carvalho,José Ruy Porto de
González,Antonio Paz
author2_role author
author
dc.contributor.author.fl_str_mv Vieira,Sidney Rosa
Carvalho,José Ruy Porto de
González,Antonio Paz
dc.subject.por.fl_str_mv Semivariograms
stationarity
topography
scale of variation
topic Semivariograms
stationarity
topography
scale of variation
description The semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to choose a better fit in distinct regions of the semivariogram.
publishDate 2010
dc.date.none.fl_str_mv 2010-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500011
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500011
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0006-87052010000500011
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto Agronômico de Campinas
publisher.none.fl_str_mv Instituto Agronômico de Campinas
dc.source.none.fl_str_mv Bragantia v.69 suppl.0 2010
reponame:Bragantia
instname:Instituto Agronômico de Campinas (IAC)
instacron:IAC
instname_str Instituto Agronômico de Campinas (IAC)
instacron_str IAC
institution IAC
reponame_str Bragantia
collection Bragantia
repository.name.fl_str_mv Bragantia - Instituto Agronômico de Campinas (IAC)
repository.mail.fl_str_mv bragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br
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