&lt;b&gt;Zero-inflated beta regression model for leaf citrus canker incidence in orange genotypes grafted onto different rootstocks

Gonzatto, Oilson Alberto; Guedes, Terezinha Aparecida; Gonçalves-Zuliane, Aline Maria Orbolato; Nunes, William Mário de Carvalho

doi:10.4025/actascibiolsci.v39i2.33063

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…Misalkan parameter baru yaitu 𝜋 = 𝑎/(𝑎 + 𝑏), sehingga 0 < 𝜋 < 1 dan misalkan 𝜙 = 𝑎 + 𝑏 maka 𝜙 > 0, sehingga substitusi kebalikannya yaitu 𝑎 = 𝜙𝜋 dimana 𝑎 > 0 dan 𝑏 = 𝜙(1 − 𝜋) dimana 𝑏 > 0. Dengan mempertimbangkan parameterisasi baru, fungsi densitas peluang dari distribusi beta yaitu 𝐵(𝑎, 𝑏) dinotasikan menjadi 𝐵(𝜋, 𝜙) dan dapat dituliskan sebagai berikut [5]:…”

Section: Bunclassified

“…Misalkan 𝑦 1 , … , 𝑦 𝑛 adalah variabel respon acak sehingga setiap 𝑦 𝑖 , untuk 𝑖 = 1, … , 𝑛, memiliki fungsi densitas peluang pada persamaan (2.11) dengan parameter 𝛿 = 𝛿 𝑖 , 𝜋 = 𝜋 𝑖 , dan 𝜙 = 𝜙 𝑖 . Diasumsikan bahwa 𝛿 = 𝛿 𝑖 , 𝜋 = 𝜋 𝑖 , dan 𝜙 = 𝜙 𝑖 didefinisikan sebagai fungsi hubung logit dari parameter 𝛿, 𝜋, dan 𝜙 dapat dimodelkan menjadi [5]:…”

Section: Definisi Model Dan Taksiran Parameter Regresi Beziunclassified

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Implementasi Zero Inflated Beta Regression Model pada Proporsi Kematian Ibu di Kota Bandung Tahun 2020

Kaulika,

Hajarisman

2023

BCSS

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Abstract. Zero inflated beta is a mixture of the continous distribution on (0, 1) and the generated distribution which can produce a non-negative probability to 0. Zero Inflated Beta Regression (BeZI) is a method that can handle or model data that has a high proportion of zeros or there are excess zeros in the data. In this study, the response variable y has a mix between the beta distribution and the point mass at zero. Estimation of the regression parameters from the zero inflated beta regression model uses the Maximum Likelihood Estimation (MLE), where the estimation process is solved numerically. The numerical method used is the Fisher’s scoring method based on the score vector and the Fisher Information matrix to estimate the parameters of the maternal mortality rate in the city of Bandung in 2020. The results of the research on the count regression model show that the percentage variable K1 has a negative effect on the proportion of maternal deaths in Bandung City in 2020, while in the zero inflation model it is found that there are no variables that have an influence on the proportion when maternal deaths do not occur. Abstrak. Zero inflated beta merupakan campuran distribusi kontinu pada (0, 1) dan distribusi yang dibangkitkan dimana dapat menghasilkan probabilitas non-negatif ke 0. Zero Inflated Beta Regression (BeZI) merupakan metode yang dapat menangani atau memodelkan suatu data yang memiliki proporsi nol yang tinggi atau terdapat excess zero dalam data. Dalam skripsi ini, variabel respon memiliki percampuran antara distribusi beta dan titik massa pada nol. Penaksiran parameter regresi dari model regresi zero inflated beta menggunakan Maximum Likelihood Estimation (MLE), dimana proses penaksirannya diselesaikan secara numerik. Metode numerik yang digunakan yaitu metode Fisher’s scoring berdasarkan pada vektor skor dan matriks informasi Fisher untuk menaksir parameter dari angka kematian ibu di kota bandung tahun 2020. Hasil penelitian pada model count regression diperoleh bahwa variabel persentase K1 memiliki pengaruh negatif terhadap proporsi kematian ibu Kota Bandung tahun 2020, sedangkan pada model zero inflation diperoleh bahwa tidak ada variabel yang memiliki pengaruh terhadap proporsi pada saat tidak terjadinya kematian ibu.

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Section: Bunclassified

Section: Definisi Model Dan Taksiran Parameter Regresi Beziunclassified

Implementasi Zero Inflated Beta Regression Model pada Proporsi Kematian Ibu di Kota Bandung Tahun 2020

Kaulika,

Hajarisman

2023

BCSS

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Voluntary fishing restrictions alone do not promote growth of bryozoan-dominated biogenic habitat on the Otago shelf, southeastern New Zealand

Mello

Smith

Wood

2021

ICES Journal of Marine Science

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On the continental shelf, New Zealand bryozoans dominate ecologically-important three-dimensional benthic habitat providing structural complexity which hosts a wide variety of fauna, including economically valuable species (e.g. oysters and blue cod). The association between these species and bryozoan-dominated biogenic habitat commonly results in trawling damage to the benthos; eliminating pressure from destructive fishing practices could support bryozoan regrowth. In 2002, a voluntary fishing restriction was designated over part of one such bryozoan-dominated biogenic habitat, but the efficacy of this ban has not been assessed. Statutory marine protected areas have been proposed in the same area; they aim to achieve bryozoan protection and recovery. A comparison of the bryozoan fauna using benthic images from 2003 and 2019 from the Otago shelf, South Island, New Zealand/Te Waipounamu, Aotearoa shows that a 17-year voluntary fishing ban has been ineffective at increasing the cover and richness of bryozoan-dominated biogenic habitat on the Otago shelf. This study provides a baseline for future monitoring and develops useful metrics for recovery, while calling for further research on the biology and ecology of habitat-forming bryozoans.

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Determinants of agricultural commercialization in smallholder farmers in Zimbabwe: The case of Zhombe North Rural District

Pamela¹,

Faustino²,

J.³

et al. 2022

J. Dev. Agric. Econ.

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Agricultural commercialization raises farm incomes and improves living standards inAfrican farming populations. Despite its importance, it remains low in Africa. Limited studies in agricultural commercialization have explored different tools for analysis given the agricultural commercialization indicators with zeros and fractions. This paper addresses methodological issue and adds literature on factors affecting agricultural commercialization. Agricultural commercialization is explored in Zhombe North Rural District using 2017/2018 cross-sectional data collected from 165 households. The zeroinflated beta regression model was used to find the drivers of agricultural commercialization. Crop output market participation share served as a proxy for agricultural commercialization. Land size, fertilizer use, use of credit, and certified seed proportion had significant positive effects on agricultural commercialization. In contrast, household head age, food cropping land size, and off-farm employment significantly influenced agricultural commercialization. The results for the model are similar to the results in previous studies using the Tobit model. The study recommends policies that promote the availability and usage of inputs to improve agricultural commercialization in the study area.

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<b>Zero-inflated beta regression model for leaf citrus canker incidence in orange genotypes grafted onto different rootstocks

Cited by 3 publications

References 27 publications

Implementasi Zero Inflated Beta Regression Model pada Proporsi Kematian Ibu di Kota Bandung Tahun 2020

Implementasi Zero Inflated Beta Regression Model pada Proporsi Kematian Ibu di Kota Bandung Tahun 2020

Voluntary fishing restrictions alone do not promote growth of bryozoan-dominated biogenic habitat on the Otago shelf, southeastern New Zealand

Determinants of agricultural commercialization in smallholder farmers in Zimbabwe: The case of Zhombe North Rural District

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