Multiphasic Individual Growth Models in Random Environments
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/7122 https://doi.org/10.1007/s11009-010-9172-0 |
Resumo: | The evolution of the growth of an individual in a random environment can be described through stochastic differential equations of the form dY(t) = β(α − Y(t))dt + σdW(t), where Y(t)= h(X t ), X(t) is the size of the individual at age t, h is a strictly increasing continuously differentiable function, α = h(A), where A is the average asymptotic size, and β represents the rate of approach to maturity. The parameter σ measures the intensity of the effect of random fluctuations on growth and W(t) is the standard Wiener process. We have previously applied this monophasic model, in which there is only one functional form describing the average dynamics of the complete growth curve, and studied the estimation issues. Here, we present the generalization of the above stochastic model to the multiphasic case, in which we consider that the growth coefficient β assumes different values for different phases of the animal’s life. For simplicity, we consider two phases with growth coefficients β1 and β2. Results and methods are illustrated using bovine growth data. |
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7160 |
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Multiphasic Individual Growth Models in Random EnvironmentsMultiphasic growth modelsStochastic differential equationsEstimationCattle weightThe evolution of the growth of an individual in a random environment can be described through stochastic differential equations of the form dY(t) = β(α − Y(t))dt + σdW(t), where Y(t)= h(X t ), X(t) is the size of the individual at age t, h is a strictly increasing continuously differentiable function, α = h(A), where A is the average asymptotic size, and β represents the rate of approach to maturity. The parameter σ measures the intensity of the effect of random fluctuations on growth and W(t) is the standard Wiener process. We have previously applied this monophasic model, in which there is only one functional form describing the average dynamics of the complete growth curve, and studied the estimation issues. Here, we present the generalization of the above stochastic model to the multiphasic case, in which we consider that the growth coefficient β assumes different values for different phases of the animal’s life. For simplicity, we consider two phases with growth coefficients β1 and β2. Results and methods are illustrated using bovine growth data.2013-01-08T12:29:32Z2013-01-082012-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/7122http://hdl.handle.net/10174/7122https://doi.org/10.1007/s11009-010-9172-0engCIMApasf@uevora.ptbraumann@uevora.ptcroquete@uevora.pt340Filipe, Patrícia A.Braumann, Carlos A.Roquete, Carlos J.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:RCAAP2024-01-03T18:47:04Zoai:dspace.uevora.pt:10174/7122Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:01:43.521246Repositório 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 |
Multiphasic Individual Growth Models in Random Environments |
title |
Multiphasic Individual Growth Models in Random Environments |
spellingShingle |
Multiphasic Individual Growth Models in Random Environments Filipe, Patrícia A. Multiphasic growth models Stochastic differential equations Estimation Cattle weight |
title_short |
Multiphasic Individual Growth Models in Random Environments |
title_full |
Multiphasic Individual Growth Models in Random Environments |
title_fullStr |
Multiphasic Individual Growth Models in Random Environments |
title_full_unstemmed |
Multiphasic Individual Growth Models in Random Environments |
title_sort |
Multiphasic Individual Growth Models in Random Environments |
author |
Filipe, Patrícia A. |
author_facet |
Filipe, Patrícia A. Braumann, Carlos A. Roquete, Carlos J. |
author_role |
author |
author2 |
Braumann, Carlos A. Roquete, Carlos J. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Filipe, Patrícia A. Braumann, Carlos A. Roquete, Carlos J. |
dc.subject.por.fl_str_mv |
Multiphasic growth models Stochastic differential equations Estimation Cattle weight |
topic |
Multiphasic growth models Stochastic differential equations Estimation Cattle weight |
description |
The evolution of the growth of an individual in a random environment can be described through stochastic differential equations of the form dY(t) = β(α − Y(t))dt + σdW(t), where Y(t)= h(X t ), X(t) is the size of the individual at age t, h is a strictly increasing continuously differentiable function, α = h(A), where A is the average asymptotic size, and β represents the rate of approach to maturity. The parameter σ measures the intensity of the effect of random fluctuations on growth and W(t) is the standard Wiener process. We have previously applied this monophasic model, in which there is only one functional form describing the average dynamics of the complete growth curve, and studied the estimation issues. Here, we present the generalization of the above stochastic model to the multiphasic case, in which we consider that the growth coefficient β assumes different values for different phases of the animal’s life. For simplicity, we consider two phases with growth coefficients β1 and β2. Results and methods are illustrated using bovine growth data. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-03-01T00:00:00Z 2013-01-08T12:29:32Z 2013-01-08 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/7122 http://hdl.handle.net/10174/7122 https://doi.org/10.1007/s11009-010-9172-0 |
url |
http://hdl.handle.net/10174/7122 https://doi.org/10.1007/s11009-010-9172-0 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
CIMA pasf@uevora.pt braumann@uevora.pt croquete@uevora.pt 340 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799136500683636736 |