Modelling Individual Growth in Random Environments

Detalhes bibliográficos
Autor(a) principal: Filipe, Patrícia A.
Data de Publicação: 2008
Outros Autores: Braumann, Carlos A.
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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spelling 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
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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
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pasf@uevora.pt
braumann@uevora.pt
336
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