Richards growth model and viability indicators for populations subject to interventions
Autor(a) principal: | |
---|---|
Data de Publicação: | 2010 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652010000400028 |
Resumo: | In this work we study the problem of modeling identification of a population employing a discrete dynamic model based on the Richards growth model. The population is subjected to interventions due to consumption, such as hunting or farming animals. The model identification allows us to estimate the probability or the average time for a population number to reach a certain level. The parameter inference for these models are obtained with the use of the likelihood profile technique as developed in this paper. The identification method here developed can be applied to evaluate the productivity of animal husbandry or to evaluate the risk of extinction of autochthon populations. It is applied to data of the Brazilian beef cattle herd population, and the the population number to reach a certain goal level is investigated. |
id |
ABC-1_7ae4820696d8dc76423e1161ef04706e |
---|---|
oai_identifier_str |
oai:scielo:S0001-37652010000400028 |
network_acronym_str |
ABC-1 |
network_name_str |
Anais da Academia Brasileira de Ciências (Online) |
repository_id_str |
|
spelling |
Richards growth model and viability indicators for populations subject to interventionsRichards growth modelpopulation riskharvested populationsparametric estimatelikelihood profile functionIn this work we study the problem of modeling identification of a population employing a discrete dynamic model based on the Richards growth model. The population is subjected to interventions due to consumption, such as hunting or farming animals. The model identification allows us to estimate the probability or the average time for a population number to reach a certain level. The parameter inference for these models are obtained with the use of the likelihood profile technique as developed in this paper. The identification method here developed can be applied to evaluate the productivity of animal husbandry or to evaluate the risk of extinction of autochthon populations. It is applied to data of the Brazilian beef cattle herd population, and the the population number to reach a certain goal level is investigated.Academia Brasileira de Ciências2010-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652010000400028Anais da Academia Brasileira de Ciências v.82 n.4 2010reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/S0001-37652010000400028info:eu-repo/semantics/openAccessLoibel,SeleneAndrade,Marinho G.Val,João B.R. doFreitas,Alfredo R. deeng2011-02-28T00:00:00Zoai:scielo:S0001-37652010000400028Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2011-02-28T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Richards growth model and viability indicators for populations subject to interventions |
title |
Richards growth model and viability indicators for populations subject to interventions |
spellingShingle |
Richards growth model and viability indicators for populations subject to interventions Loibel,Selene Richards growth model population risk harvested populations parametric estimate likelihood profile function |
title_short |
Richards growth model and viability indicators for populations subject to interventions |
title_full |
Richards growth model and viability indicators for populations subject to interventions |
title_fullStr |
Richards growth model and viability indicators for populations subject to interventions |
title_full_unstemmed |
Richards growth model and viability indicators for populations subject to interventions |
title_sort |
Richards growth model and viability indicators for populations subject to interventions |
author |
Loibel,Selene |
author_facet |
Loibel,Selene Andrade,Marinho G. Val,João B.R. do Freitas,Alfredo R. de |
author_role |
author |
author2 |
Andrade,Marinho G. Val,João B.R. do Freitas,Alfredo R. de |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Loibel,Selene Andrade,Marinho G. Val,João B.R. do Freitas,Alfredo R. de |
dc.subject.por.fl_str_mv |
Richards growth model population risk harvested populations parametric estimate likelihood profile function |
topic |
Richards growth model population risk harvested populations parametric estimate likelihood profile function |
description |
In this work we study the problem of modeling identification of a population employing a discrete dynamic model based on the Richards growth model. The population is subjected to interventions due to consumption, such as hunting or farming animals. The model identification allows us to estimate the probability or the average time for a population number to reach a certain level. The parameter inference for these models are obtained with the use of the likelihood profile technique as developed in this paper. The identification method here developed can be applied to evaluate the productivity of animal husbandry or to evaluate the risk of extinction of autochthon populations. It is applied to data of the Brazilian beef cattle herd population, and the the population number to reach a certain goal level is investigated. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652010000400028 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652010000400028 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0001-37652010000400028 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.82 n.4 2010 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
_version_ |
1754302857705684992 |