Estimation of Zero-Inflation Parameter in Zero-Inflated Poisson Model

2018 ◽  
Vol 56 (2) ◽  
pp. 135-140
Author(s):  
K.M.Sakthi vel ◽  
◽  
C.S.Raji tha
Keyword(s):  
Poisson Model ◽  
Zero Inflation ◽  
Inflation Parameter

scholarly journals Analysis of Infant Congenital Malformation Data using the Bayesian Count Regression

2021 ◽  
Keyword(s):  
Birth Weight ◽  
Congenital Malformations ◽  
Regression Models ◽  
Significant Proportion ◽  
Poisson Model ◽  
Health Data ◽  
Zero Inflation ◽  
Factors Affecting ◽  
Parental Consanguinity ◽  
Better Than

Background: Congenital malformations are one of the most important and common types of anomalies in infants, which are one of the main causes of disability and mortality in children. Objectives: This study aimed to investigate the risk factors affecting the incidence of congenital malformations, as well as the number of different infant anomalies recorded in neonatal health data in Khoy, Iran, during 2017. Methods: In this study, all neonates born in the maternity wards of hospitals in Khoy, Iran, during 2017 were evaluated in terms of gender, weight, and parental consanguinity. Hurdle and Zero-inflation approaches were utilized for the double Poisson model. Moreover, the data were collected using some checklists, and the analyses were performed in R-3-6-1 software. Result: According to the results of the present study, the Hurdle approach was better than Zero-inflation. The birth weight and parental consanguinity affected the incidence of congenital malformations in infants. Conclusion: Given that a significant proportion of infants are born without any congenital malformations, it is important to use count regression models based on excess zero approaches to assess congenital malformations. It is also necessary to take steps to reduce consanguineous marriages and the number of infants with low-birth-weight to prevent congenital malformations.

Tests for zero inflation in a bivariate zero-inflated Poisson model

2009 ◽  
Vol 63 (4) ◽  
pp. 400-417 ◽  
Author(s):  
JungBok Lee ◽  
Byoung Cheol Jung ◽  
Seo Hoon Jin
Keyword(s):  
Poisson Model ◽  
Zero Inflation

scholarly journals Analysis of factors causing the number of poor people in DKI Jakarta using spatial autoregressive Poisson model

2021 ◽  
Author(s):  
Siti Rohmah Rohimah ◽  
Qorry Meidianingsih ◽  
Nabilah Ninda Nur Azizah ◽  
Ahmad Syauqy Baihaqy
Keyword(s):  
Poisson Model ◽  
Poor People ◽  
Spatial Autoregressive

scholarly journals Effects of Ad-hoc Data Truncation and Homogeneous Preferences on Recreational Demand and Values: An Application to the George Washington and Jefferson National Forests

2021 ◽  
pp. 1-15
Author(s):  
Kavita Sardana ◽  
John C. Bergstrom ◽  
J. M. Bowker
Keyword(s):  
Latent Class ◽  
Ad Hoc ◽  
Cost Model ◽  
Consumer Surplus ◽  
Poisson Model ◽  
Travel Cost ◽  
National Forests ◽  
Heterogeneous Preferences ◽  
George Washington ◽  
Travel Cost Model

Abstract We estimate a travel cost model for the George Washington & Jefferson National Forests using an On-Site Latent Class Poisson Model. We show that the constraints of ad-hoc truncation and homogenous preferences significantly impact consumer surplus estimates derived from the on-site travel cost model. By relaxing the constraints, we show that more than one class of visitors with unique preferences exists in the population. The resulting demand functions, price responsive behaviors, and consumer surplus estimates reflect differences across these classes of visitors. With heterogeneous preferences, a group of ‘local residents’ exists with a probability of 8% and, on average take 113 visits.

scholarly journals Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 282
Author(s):  
Mabel Morales-Otero ◽  
Vicente Núñez-Antón
Keyword(s):  
Infant Mortality ◽  
Count Data ◽  
Spatial Dependence ◽  
Poisson Model ◽  
Mortality Rates ◽  
Estimation Methods ◽  
Neighborhood Structure ◽  
Specific Context ◽  
Count Data Models ◽  
Conditional Mean

In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag–York–Mollié (BYM) models. These overdispersed models assume that excess of dispersion in the data may be partially caused from the possible spatial dependence existing among the different spatial units. Thus, specific regression structures are then proposed both for the conditional mean and for the dispersion parameter in the models, including covariates, as well as an assumed spatial neighborhood structure. We focus on the case of response variables following a Poisson distribution, specifically concentrating on the spatial generalized conditional normal overdispersion Poisson model. Models were fitted by making use of the Markov Chain Monte Carlo (MCMC) and Integrated Nested Laplace Approximation (INLA) algorithms in the specific context of Bayesian estimation methods.

scholarly journals Intra-urban differentials of congenital and acquired syphilis and syphilis in pregnant women in an urban area in northeastern Brazil

2021 ◽  
Author(s):  
Talita Araujo de Souza ◽  
Karen Kaline Teixeira ◽  
Reginaldo Lopes Santana ◽  
Cinthia Barros Penha ◽  
Arthur de Almeida Medeiros ◽  
...  
Keyword(s):  
Relative Risk ◽  
Pregnant Women ◽  
Congenital Syphilis ◽  
Kernel Density ◽  
Poisson Model ◽  
Northeastern Brazil ◽  
Smoothing Function ◽  
Density Estimator ◽  
Epidemic Disease ◽  
Peripheral Areas

Abstract Background Currently syphilis is considered an epidemic disease worldwide. The objective of this study was to identify intra-urban differentials in the occurrence of congenital and acquired syphilis and syphilis in pregnant women in the city of Natal, in northeast Brazil. Methods Cases of syphilis recorded by the municipal surveillance system from 1 January 2011 to 30 December 2018 were analysed. Spatial statistical analyses were performed using the kernel density estimator of the quadratic smoothing function (weighted). SaTScan software was applied for the calculation of risk based on a discrete Poisson model. Results There were 2163 cases of acquired syphilis, 738 cases of syphilis in pregnant women and 1279 cases of congenital syphilis. Kernel density maps showed that the occurrence of cases is more prevalent in peripheral areas and in areas with more precarious urban infrastructure. In 2011–2014 and 2015–2018, seven statistically significant clusters of acquired syphilis were identified. From 2011 to 2014, the most likely cluster had a relative risk of 3.54 (log likelihood ratio [LLR] 38 895; p<0.001) and from 2015 to 2018 the relative risk was 0.54 (LLR 69 955; p<0.001). Conclusions In the municipality of Natal, there was a clustered pattern of spatial distribution of syphilis, with some areas presenting greater risk for the occurrence of new cases.

Neutral-Carrier Ion-Selective Electrodes Assessed by the Nernst–Planck–Poisson Model

2015 ◽  
Vol 87 (17) ◽  
pp. 8665-8672 ◽  
Author(s):  
Jerzy J. Jasielec ◽  
Tomasz Sokalski ◽  
Robert Filipek ◽  
Andrzej Lewenstam
Keyword(s):  
Poisson Model ◽  
Ion Selective Electrodes ◽  
Neutral Carrier
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