FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST

Detalhes bibliográficos
Autor(a) principal: Orellana, Enrique
Data de Publicação: 2017
Outros Autores: Figueiredo Filho, Afonso, Netto, Sylvio Péllico, Dias, Andrea Nogueira
Tipo de documento: Artigo
Idioma: por
Título da fonte: Ciência Florestal (Online)
Texto Completo: https://periodicos.ufsm.br/cienciaflorestal/article/view/28668
Resumo: The aim of this work was to evaluate the performance of the probability density functions with different fitting procedures and statistical evaluation to describe the diameter distribution of a Mixed Ombrophyllous Forest fragment. The study area is part of the Irati National Forest (FLONA), in Parana State. Data used were derived from 25 permanent 1-ha plots (100 m x 100m) established and measured in 2002 and re-measured in 2005 and 2008. The fittings were done considering all the species sampled on the re-measurement in 2008. Beta, Weibull 2 and 3 Parameters and Exponential Meyer I and II functions were tested, employing Moments and Maximum Likelihood methods for Beta and Percentiles and Maximum Likelihood for Weibull 2 and 3 Parameters. The Nonlinear Programming was used as an attempt to improve the fittings, except for Meyer model. To evaluate the fittings, the goodness-of-fit tests Kolmogorov-Smirnov (K-S) and Hollander-Proschan (H-P) were used, as well as, the Standard Error (%), Reynolds Index (IR) and Residual Dispersion. The results showed that Weibull 3P function was the best to describe the diameter distribution for the forest as a whole, however the Beta function showed satisfactory results, and it can also be used to evaluate the diameter distribution for the studied area. About the statistics used, it was observed that Reynolds Index presented good results to evaluate the performance to probability density functions and, for the interval class used, the Kolmogorov-Smirnov test presented a higher number of good fitness values when compared with Hollander-Proschan test, nevertheless the K-S is sensible when the frequency is high, causing a non-adherence.
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spelling FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FORESTMÉTODOS DE AJUSTE E PROCEDIMENTOS DE SELEÇÃO DE FUNÇÕES PROBABILÍSTICAS PARA MODELAR A DISTRIBUIÇÃO DIAMÉTRICA EM FLORESTA NATIVA DE ARAUCÁRIAstatistical indicesnonlinear programmingforest structure.índices estatísticosprogramação não linearestrutura florestal.The aim of this work was to evaluate the performance of the probability density functions with different fitting procedures and statistical evaluation to describe the diameter distribution of a Mixed Ombrophyllous Forest fragment. The study area is part of the Irati National Forest (FLONA), in Parana State. Data used were derived from 25 permanent 1-ha plots (100 m x 100m) established and measured in 2002 and re-measured in 2005 and 2008. The fittings were done considering all the species sampled on the re-measurement in 2008. Beta, Weibull 2 and 3 Parameters and Exponential Meyer I and II functions were tested, employing Moments and Maximum Likelihood methods for Beta and Percentiles and Maximum Likelihood for Weibull 2 and 3 Parameters. The Nonlinear Programming was used as an attempt to improve the fittings, except for Meyer model. To evaluate the fittings, the goodness-of-fit tests Kolmogorov-Smirnov (K-S) and Hollander-Proschan (H-P) were used, as well as, the Standard Error (%), Reynolds Index (IR) and Residual Dispersion. The results showed that Weibull 3P function was the best to describe the diameter distribution for the forest as a whole, however the Beta function showed satisfactory results, and it can also be used to evaluate the diameter distribution for the studied area. About the statistics used, it was observed that Reynolds Index presented good results to evaluate the performance to probability density functions and, for the interval class used, the Kolmogorov-Smirnov test presented a higher number of good fitness values when compared with Hollander-Proschan test, nevertheless the K-S is sensible when the frequency is high, causing a non-adherence.Este trabalho teve como objetivo avaliar o desempenho das funções densidade de probabilidade (fdp) com diferentes procedimentos de ajustes e estatísticas de avaliação, a fim de expressar a distribuição diamétrica de um fragmento de Floresta Ombrófila Mista. A área de estudo faz parte da Floresta Nacional de Irati (FLONA), estado do Paraná. Os dados utilizados são provenientes de 25 parcelas permanentes de 1 ha (100 m x 100 m), que foram instaladas e medidas em 2002 e remedidas em 2005 e 2008. Os ajustes foram feitos considerando todas as espécies amostradas na remedição de 2008. Foram testadas as funções Beta, Weibull 2 e 3 Parâmetros e Exponencial de Meyer (tipos I e II), empregando-se os métodos de ajustes dos Momentos e da Máxima Verossimilhança para a função Beta e Percentis e Máxima Verossimilhança para a função Weibull 2 e 3 Parâmetros. A Programação Não Linear foi utilizada como tentativa de melhorar os ajustes realizados das funções, exceto para Meyer. Para avaliação dos ajustes, foram aplicados os testes de aderência de Kolmogorov-Smirnov (K-S) e Hollander-Proschan (H-P), além do Erro Padrão de Estimativa (%), índice de Reynolds (IR) e análise de resíduos. Os resultados indicaram que a função Weibull 3P ajustada pelo método da Máxima Verossimilhança foi a melhor para descrever a distribuição diamétrica da floresta como um todo, no entanto, o método dos Percentis apresentou resultados similares. A função Beta apresentou resultados satisfatórios, podendo também ser empregada para avaliar a distribuição diamétrica da área de estudo. Quanto às estatísticas utilizadas, o índice de Reynolds mostrou ser uma ferramenta estatística com boa performance para selecionar funções densidade de probabilidade. Para o intervalo de classe utilizado, o teste Kolmogorov-Smirnov apresentou um maior número de aderências quando comparado ao teste Hollander-Proschan, porém, o teste K-S é sensível quando a frequência é alta, levando a uma não aderência.Universidade Federal de Santa Maria2017-08-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/2866810.5902/1980509828668Ciência Florestal; Vol. 27 No. 3 (2017); 969-980Ciência Florestal; v. 27 n. 3 (2017); 969-9801980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/28668/16183Copyright (c) 2017 Ciência Florestalinfo:eu-repo/semantics/openAccessOrellana, EnriqueFigueiredo Filho, AfonsoNetto, Sylvio PéllicoDias, Andrea Nogueira2017-08-31T17:21:45Zoai:ojs.pkp.sfu.ca:article/28668Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2017-08-31T17:21:45Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
MÉTODOS DE AJUSTE E PROCEDIMENTOS DE SELEÇÃO DE FUNÇÕES PROBABILÍSTICAS PARA MODELAR A DISTRIBUIÇÃO DIAMÉTRICA EM FLORESTA NATIVA DE ARAUCÁRIA
title FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
spellingShingle FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
Orellana, Enrique
statistical indices
nonlinear programming
forest structure.
índices estatísticos
programação não linear
estrutura florestal.
title_short FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
title_full FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
title_fullStr FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
title_full_unstemmed FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
title_sort FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
author Orellana, Enrique
author_facet Orellana, Enrique
Figueiredo Filho, Afonso
Netto, Sylvio Péllico
Dias, Andrea Nogueira
author_role author
author2 Figueiredo Filho, Afonso
Netto, Sylvio Péllico
Dias, Andrea Nogueira
author2_role author
author
author
dc.contributor.author.fl_str_mv Orellana, Enrique
Figueiredo Filho, Afonso
Netto, Sylvio Péllico
Dias, Andrea Nogueira
dc.subject.por.fl_str_mv statistical indices
nonlinear programming
forest structure.
índices estatísticos
programação não linear
estrutura florestal.
topic statistical indices
nonlinear programming
forest structure.
índices estatísticos
programação não linear
estrutura florestal.
description The aim of this work was to evaluate the performance of the probability density functions with different fitting procedures and statistical evaluation to describe the diameter distribution of a Mixed Ombrophyllous Forest fragment. The study area is part of the Irati National Forest (FLONA), in Parana State. Data used were derived from 25 permanent 1-ha plots (100 m x 100m) established and measured in 2002 and re-measured in 2005 and 2008. The fittings were done considering all the species sampled on the re-measurement in 2008. Beta, Weibull 2 and 3 Parameters and Exponential Meyer I and II functions were tested, employing Moments and Maximum Likelihood methods for Beta and Percentiles and Maximum Likelihood for Weibull 2 and 3 Parameters. The Nonlinear Programming was used as an attempt to improve the fittings, except for Meyer model. To evaluate the fittings, the goodness-of-fit tests Kolmogorov-Smirnov (K-S) and Hollander-Proschan (H-P) were used, as well as, the Standard Error (%), Reynolds Index (IR) and Residual Dispersion. The results showed that Weibull 3P function was the best to describe the diameter distribution for the forest as a whole, however the Beta function showed satisfactory results, and it can also be used to evaluate the diameter distribution for the studied area. About the statistics used, it was observed that Reynolds Index presented good results to evaluate the performance to probability density functions and, for the interval class used, the Kolmogorov-Smirnov test presented a higher number of good fitness values when compared with Hollander-Proschan test, nevertheless the K-S is sensible when the frequency is high, causing a non-adherence.
publishDate 2017
dc.date.none.fl_str_mv 2017-08-31
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/28668
10.5902/1980509828668
url https://periodicos.ufsm.br/cienciaflorestal/article/view/28668
identifier_str_mv 10.5902/1980509828668
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/28668/16183
dc.rights.driver.fl_str_mv Copyright (c) 2017 Ciência Florestal
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Ciência Florestal
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Florestal; Vol. 27 No. 3 (2017); 969-980
Ciência Florestal; v. 27 n. 3 (2017); 969-980
1980-5098
0103-9954
reponame:Ciência Florestal (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Florestal (Online)
collection Ciência Florestal (Online)
repository.name.fl_str_mv Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv ||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br
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