An empirical comparison of kriging methods for nonstationary spatial point prediction
This thesis compares the performance of geostatistical and geostatistical nonparametric hybrid models for providing accurate predictions together with relevant measures of prediction confidence. The key modelling theme is nonstationarity, where models that cater for nonstationary second-order effect...
| Main Author: | |
|---|---|
| Published: |
University of Newcastle Upon Tyne
2009
|
| Subjects: | |
| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492440 |
| id |
ndltd-bl.uk-oai-ethos.bl.uk-492440 |
|---|---|
| record_format |
oai_dc |
| spelling |
ndltd-bl.uk-oai-ethos.bl.uk-4924402015-03-20T05:04:15ZAn empirical comparison of kriging methods for nonstationary spatial point predictionHarris, Paul2009This thesis compares the performance of geostatistical and geostatistical nonparametric hybrid models for providing accurate predictions together with relevant measures of prediction confidence. The key modelling theme is nonstationarity, where models that cater for nonstationary second-order effects nave the potential to provide more accurate results over their stationary counterparts. A comprehensive review and comparison of this particular class of nonstationary predictors is considered missing from the literature. To facilitate this model comparison, models are calibrated to assess the spatial variation in freshwater acidification critical load data across Great Britain, which is shown to be a heterogeneous process requiring a nonstationary modelling approach.550.15195University of Newcastle Upon Tynehttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492440Electronic Thesis or Dissertation |
| collection |
NDLTD |
| sources |
NDLTD |
| topic |
550.15195 |
| spellingShingle |
550.15195 Harris, Paul An empirical comparison of kriging methods for nonstationary spatial point prediction |
| description |
This thesis compares the performance of geostatistical and geostatistical nonparametric hybrid models for providing accurate predictions together with relevant measures of prediction confidence. The key modelling theme is nonstationarity, where models that cater for nonstationary second-order effects nave the potential to provide more accurate results over their stationary counterparts. A comprehensive review and comparison of this particular class of nonstationary predictors is considered missing from the literature. To facilitate this model comparison, models are calibrated to assess the spatial variation in freshwater acidification critical load data across Great Britain, which is shown to be a heterogeneous process requiring a nonstationary modelling approach. |
| author |
Harris, Paul |
| author_facet |
Harris, Paul |
| author_sort |
Harris, Paul |
| title |
An empirical comparison of kriging methods for nonstationary spatial point prediction |
| title_short |
An empirical comparison of kriging methods for nonstationary spatial point prediction |
| title_full |
An empirical comparison of kriging methods for nonstationary spatial point prediction |
| title_fullStr |
An empirical comparison of kriging methods for nonstationary spatial point prediction |
| title_full_unstemmed |
An empirical comparison of kriging methods for nonstationary spatial point prediction |
| title_sort |
empirical comparison of kriging methods for nonstationary spatial point prediction |
| publisher |
University of Newcastle Upon Tyne |
| publishDate |
2009 |
| url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492440 |
| work_keys_str_mv |
AT harrispaul anempiricalcomparisonofkrigingmethodsfornonstationaryspatialpointprediction AT harrispaul empiricalcomparisonofkrigingmethodsfornonstationaryspatialpointprediction |
| _version_ |
1716788752673669120 |