Modeling citrus huanglongbing data using a zero-inflated negative binomial distribution/Modelagem de dados huanglongbing citricos usando um modelo binomial negativo inflacionado de zero
Zero-inflated data from field experiments can be problematic, as these data require the use of specific statistical models during the analysis process. This study utilized the zero-inflated negative binomial (ZINB) model with the log- and logistic-link functions to describe the incidence of plants w...
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| Published in | Acta scientiarum. Agronomy p. 299 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | Spanish |
| Published |
Universidade Estadual de Maringa
01.07.2016
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| Online Access | Get full text |
| ISSN | 1679-9275 |
| DOI | 10.4025/actasciagron.v38i3.28689 |
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| Abstract | Zero-inflated data from field experiments can be problematic, as these data require the use of specific statistical models during the analysis process. This study utilized the zero-inflated negative binomial (ZINB) model with the log- and logistic-link functions to describe the incidence of plants with Huanglongbing (HLB, caused by Candidatus liberibacter spp.) in commercial citrus orchards in the Northwestern Parana State, Brazil. Each orchard was evaluated at different times. The ZINB model with random effects in both link functions provided the best fit, as the inclusion of these effects accounted for variations between orchards and the numbers of diseased plants. The results of this model show that older plants exhibit a lower probability of acquiring HLB. The application of insecticides on a calendar basis or during new foliage flushes resulted in a three times larger probability of developing HLB compared with applying insecticides only when the vector was detected. Keywords: mixed model, random effect, BLUP method, EM algorithm. Em diversas areas do conhecimento, dados com excesso de zeros sao encontrados com frequencia. Para a analise de tais dados, e recomendado utilizar modelos que permitam uma contagem deste excesso de zero de forma adequada. Neste artigo, o modelo binomial negativo inflacionado de zero (ZINB) foi utilizado para descrever o numero de plantas doentes, acometidas por Huanglongbing, em pomares comercias de laranjeiras na regiao noroeste do Estado do Parana. Entretanto, deve-se levar em consideracao que cada pomar foi avaliado ao longo do tempo, sendo assim, neste contexto, o modelo ZINB com efeito aleatorio em ambas as funcoes de ligacao, logaritmica e logistica, apresentou melhor ajuste aos dados, pois a introducao destes efeitos consideraram as variacoes entre os pomares e a dependencia entre numero de plantas doentes. A partir deste modelo e possivel perceber que as plantas mais velhas tendem a apresentar menor probabilidade de adquirir a doenca. Todavia, a aplicacao de inseticidas e o manejo por calendario apresentam tres vezes mais chance de apresentar a doenca do que o manejo somente pela presenca do vetor. Palavras-chave: modelo misto, efeito aleatorio, metodo BLUP, algoritmo EM. |
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| AbstractList | Zero-inflated data from field experiments can be problematic, as these data require the use of specific statistical models during the analysis process. This study utilized the zero-inflated negative binomial (ZINB) model with the log- and logistic-link functions to describe the incidence of plants with Huanglongbing (HLB, caused by Candidatus liberibacter spp.) in commercial citrus orchards in the Northwestern Parana State, Brazil. Each orchard was evaluated at different times. The ZINB model with random effects in both link functions provided the best fit, as the inclusion of these effects accounted for variations between orchards and the numbers of diseased plants. The results of this model show that older plants exhibit a lower probability of acquiring HLB. The application of insecticides on a calendar basis or during new foliage flushes resulted in a three times larger probability of developing HLB compared with applying insecticides only when the vector was detected. Keywords: mixed model, random effect, BLUP method, EM algorithm. Em diversas areas do conhecimento, dados com excesso de zeros sao encontrados com frequencia. Para a analise de tais dados, e recomendado utilizar modelos que permitam uma contagem deste excesso de zero de forma adequada. Neste artigo, o modelo binomial negativo inflacionado de zero (ZINB) foi utilizado para descrever o numero de plantas doentes, acometidas por Huanglongbing, em pomares comercias de laranjeiras na regiao noroeste do Estado do Parana. Entretanto, deve-se levar em consideracao que cada pomar foi avaliado ao longo do tempo, sendo assim, neste contexto, o modelo ZINB com efeito aleatorio em ambas as funcoes de ligacao, logaritmica e logistica, apresentou melhor ajuste aos dados, pois a introducao destes efeitos consideraram as variacoes entre os pomares e a dependencia entre numero de plantas doentes. A partir deste modelo e possivel perceber que as plantas mais velhas tendem a apresentar menor probabilidade de adquirir a doenca. Todavia, a aplicacao de inseticidas e o manejo por calendario apresentam tres vezes mais chance de apresentar a doenca do que o manejo somente pela presenca do vetor. Palavras-chave: modelo misto, efeito aleatorio, metodo BLUP, algoritmo EM. Zero-inflated data from field experiments can be problematic, as these data require the use of specific statistical models during the analysis process. This study utilized the zero-inflated negative binomial (ZINB) model with the log- and logistic-link functions to describe the incidence of plants with Huanglongbing (HLB, caused by Candidatus liberibacter spp.) in commercial citrus orchards in the Northwestern Parana State, Brazil. Each orchard was evaluated at different times. The ZINB model with random effects in both link functions provided the best fit, as the inclusion of these effects accounted for variations between orchards and the numbers of diseased plants. The results of this model show that older plants exhibit a lower probability of acquiring HLB. The application of insecticides on a calendar basis or during new foliage flushes resulted in a three times larger probability of developing HLB compared with applying insecticides only when the vector was detected. |
| Audience | Academic |
| Author | Janeiro, Vanderly Carneiro, Jose Walter Pedroza de Almeida, Eudmar Paiva Guedes, Terezinha Aparecida Nunes, William Mario de Carvalho Mulati, Fabio |
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| Title | Modeling citrus huanglongbing data using a zero-inflated negative binomial distribution/Modelagem de dados huanglongbing citricos usando um modelo binomial negativo inflacionado de zero |
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