FITTING METHODS AND SELECTION PROCEDURES OF PROBABILISTIC FUNCTIONS TO MODEL THE DIAMETER DISTRIBUTION IN A NATIVE ARAUCARIA FOREST
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
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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Ciência Florestal (Online) |
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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 |
_version_ |
1799944132499603456 |