Modelling Individual Growth in Random Environments
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/1534 |
Resumo: | We have considered, as general models for the evolution of animal size in a random environment, stochastic differential equations of the form dY(t)=b( A-Y(t))dt+\sigma dW(t), where Y(t)=g(X(t)), X(t) is the size of an animal at time t, g is a strictly increasing function, A=g(a) where a is the asymptotic size, b>0 is a rate of approach to A, s measures the effect of random environmental fluctuations on growth, and W(t) is the Wiener process. The transient and stationary behaviours of this stochastic differential equation model are well-known. We have considered the stochastic Bertalanffy-Richards model (g(x)=x^c with c>0) and the stochastic Gompertz model (g(x)=ln x). We have studied the problems of parameter estimation for one path and also considered the extension of the estimation methods to the case of several paths, assumed to be independent. We used numerical techniques to obtain the parameters estimates through maximum likelihood methods as well as bootstrap methods. The data used for illustration is the weight of "mertolengo" cattle of the "rosilho" strand. |
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Modelling Individual Growth in Random Environmentsgrowth modelsstochastic differential equationsestimationcattle weightWe have considered, as general models for the evolution of animal size in a random environment, stochastic differential equations of the form dY(t)=b( A-Y(t))dt+\sigma dW(t), where Y(t)=g(X(t)), X(t) is the size of an animal at time t, g is a strictly increasing function, A=g(a) where a is the asymptotic size, b>0 is a rate of approach to A, s measures the effect of random environmental fluctuations on growth, and W(t) is the Wiener process. The transient and stationary behaviours of this stochastic differential equation model are well-known. We have considered the stochastic Bertalanffy-Richards model (g(x)=x^c with c>0) and the stochastic Gompertz model (g(x)=ln x). We have studied the problems of parameter estimation for one path and also considered the extension of the estimation methods to the case of several paths, assumed to be independent. We used numerical techniques to obtain the parameters estimates through maximum likelihood methods as well as bootstrap methods. The data used for illustration is the weight of "mertolengo" cattle of the "rosilho" strand.2009-04-08T16:09:37Z2009-04-082008-08-26T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject65916 bytesapplication/pdfhttp://hdl.handle.net/10174/1534http://hdl.handle.net/10174/1534engFaculdade de Economia da Universidade do Porto - Porto, PortugalModelling Individual Growth in Random Environmentssimnaonaolivrepasf@uevora.ptbraumann@uevora.pt336Filipe, Patrícia A.Braumann, Carlos A.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T18:37:13Zoai:dspace.uevora.pt:10174/1534Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:57:24.539110Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Modelling Individual Growth in Random Environments |
title |
Modelling Individual Growth in Random Environments |
spellingShingle |
Modelling Individual Growth in Random Environments Filipe, Patrícia A. growth models stochastic differential equations estimation cattle weight |
title_short |
Modelling Individual Growth in Random Environments |
title_full |
Modelling Individual Growth in Random Environments |
title_fullStr |
Modelling Individual Growth in Random Environments |
title_full_unstemmed |
Modelling Individual Growth in Random Environments |
title_sort |
Modelling Individual Growth in Random Environments |
author |
Filipe, Patrícia A. |
author_facet |
Filipe, Patrícia A. Braumann, Carlos A. |
author_role |
author |
author2 |
Braumann, Carlos A. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Filipe, Patrícia A. Braumann, Carlos A. |
dc.subject.por.fl_str_mv |
growth models stochastic differential equations estimation cattle weight |
topic |
growth models stochastic differential equations estimation cattle weight |
description |
We have considered, as general models for the evolution of animal size in a random environment, stochastic differential equations of the form dY(t)=b( A-Y(t))dt+\sigma dW(t), where Y(t)=g(X(t)), X(t) is the size of an animal at time t, g is a strictly increasing function, A=g(a) where a is the asymptotic size, b>0 is a rate of approach to A, s measures the effect of random environmental fluctuations on growth, and W(t) is the Wiener process. The transient and stationary behaviours of this stochastic differential equation model are well-known. We have considered the stochastic Bertalanffy-Richards model (g(x)=x^c with c>0) and the stochastic Gompertz model (g(x)=ln x). We have studied the problems of parameter estimation for one path and also considered the extension of the estimation methods to the case of several paths, assumed to be independent. We used numerical techniques to obtain the parameters estimates through maximum likelihood methods as well as bootstrap methods. The data used for illustration is the weight of "mertolengo" cattle of the "rosilho" strand. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-08-26T00:00:00Z 2009-04-08T16:09:37Z 2009-04-08 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/1534 http://hdl.handle.net/10174/1534 |
url |
http://hdl.handle.net/10174/1534 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Faculdade de Economia da Universidade do Porto - Porto, Portugal Modelling Individual Growth in Random Environments sim nao nao livre pasf@uevora.pt braumann@uevora.pt 336 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
65916 bytes application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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