{"id":{"repo_id":"glasgow","oai_identifier":"oai:theses.gla.ac.uk:1450"},"canonical_url":"https://search.dev.ndltd.org/etd/glasgow/oai:theses.gla.ac.uk:1450","repository":{"repo_id":"glasgow","name":"University of Glasgow","base_url":"https://theses.gla.ac.uk/cgi/oai2"},"display":{"title":"Statistical modelling of environmental trends over both time and space","abstract":"The analysis of environmental data represents an opportunity to use statistical tools to provide a better understanding of changes over time and space, making it easier to tackle problems such as pollution, water quality or climate change. The analysis of environmental data requires methodologies that allow us to ﬁt models capable of explaining seasonal patterns and changes observed over time and space. The work developed in this thesis is centred on the modelling of trends over time and space simultaneously. 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The analysis of this information could be carried out in a marginal manner over time and space; however the main ob jective of this thesis is to ﬁt a model using both time and space simultaneously to be able to provide a closer representation of environmental data.","abstract_has_math":false,"creators":["Rincon, Francisco Andres"],"institution":"University of Glasgow","degree_name":null,"degree_level":"MSc(R)","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010","date_published":"2010","updated_at":"2026-07-24T02:23:57Z","subjects":["QA Mathematics"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Rincon, Francisco Andres"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2010"]},{"key":"dc:date.issued","label":"Date","values":["2010"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Glasgow"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://theses.gla.ac.uk/1450/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["MSc(R)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["QA Mathematics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://theses.gla.ac.uk/1450/1/2009RinconMSc.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The analysis of environmental data represents an opportunity to use statistical tools to provide a better understanding of changes over time and space, making it easier to tackle problems such as pollution, water quality or climate change. The analysis of environmental data requires methodologies that allow us to ﬁt models capable of explaining seasonal patterns and changes observed over time and space. The work developed in this thesis is centred on the modelling of trends over time and space simultaneously. The analysis of this information could be carried out in a marginal manner over time and space; however the main ob jective of this thesis is to ﬁt a model using both time and space simultaneously to be able to provide a closer representation of environmental data."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Statistical modelling of environmental trends over both time and space"]}]}],"canonical_facts":{"dc:creator":["Rincon, Francisco Andres"],"dc:date":["2010"],"dc:date.issued":["2010"],"dc:description.abstract":["The analysis of environmental data represents an opportunity to use statistical tools to provide a better understanding of changes over time and space, making it easier to tackle problems such as pollution, water quality or climate change. 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The analysis of this information could be carried out in a marginal manner over time and space; however the main ob jective of this thesis is to ﬁt a model using both time and space simultaneously to be able to provide a closer representation of environmental data."],"dc:format":["application/pdf"],"dc:identifier.uri":["https://theses.gla.ac.uk/1450/1/2009RinconMSc.pdf"],"dc:language":["en"],"dc:publisher.institution":["University of Glasgow"],"dc:relation.isreferencedby":["https://theses.gla.ac.uk/1450/"],"dc:subject":["QA Mathematics"],"dc:title":["Statistical modelling of environmental trends over both time and space"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["MSc(R)"]},"updated_at":"2026-07-24T02:23:57Z"}