Tests for Detecting Overdispersion in the Positive Poisson Regression Model

Gurmu, Shiferaw

doi:10.1080/07350015.1991.10509847

Cited by 59 publications

(55 citation statements)

References 24 publications

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“…The Poisson count regression model (PCRM), negative binomial model and simple linear regression (OLS) can be used. The first two models have strict requirements that give them operational problems as follows: for the Poisson distribution, it assumes that the mean and variance of the dependent variable(s) are equal, but normally as a result of over-dispersion; the conditional variance of the dependent variable exceeds the conditional mean [22].…”

Section: A Theoretical Frameworkmentioning

confidence: 99%

Determinants of Rural Farmers’ Adoption of Climate Change Adaptation Strategies: Evidence from the Amathole District Municipality, Eastern Cape Province, South Africa

Taruvinga¹,

Visser²,

Zhou³

2016

IJESD

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Abstract-There is consensus that rural farmers' livelihoods are vulnerable to climate change. Also, literature suggests that locally driven adaptations are critical complementary strategies that can be targeted to reduce the negative effects of climate change in the short-run. Thus far, through using a cross sectional survey sample of 200 rural farmers from the Amathole district municipality of the Eastern Cape Province of South Africa, the paper estimated farmers' climate change adaptation strategies, adaptation portfolio diversity and factors that condition farmers' adoption behavior. The results reveal several crop, livestock and non-farm based adaptation strategies skewed in favour of crop and non-farm floral based techniques. The results further indicate that rural farmers in general are low adopters of climate change adaptation strategies with poor adaptation portfolio diversity. Regression estimates reveal several socio-economic and institutional factors as drivers of adoption and adaptation portfolio diversity worth targeting to promote the ability of rural farmers to cope with climate change.

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Section: A Theoretical Frameworkmentioning

confidence: 99%

Determinants of Rural Farmers’ Adoption of Climate Change Adaptation Strategies: Evidence from the Amathole District Municipality, Eastern Cape Province, South Africa

Taruvinga¹,

Visser²,

Zhou³

2016

IJESD

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“…where now 13 Gurmu (1991), Grogger and Carson (1991), Gurmu and Trivedi (1992), among others, have commented on these models. Recent application in order to look for some evidence of the presence of reputation in the return to tourist destination can be found in Ledesma et al (2005).…”

Section: Models For a Subsamplementioning

confidence: 99%

An analysis of count data models for the study of exclusivity in wine consumption

et al. 2009

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Several models which analyze count data have been proposed in econometric literature. These models allow the discrete, non-negative nature of specific phenomena of interest to be gathered in a appropriate way and can be useful for the explanation of specific preference structures among individuals. In this work, an analysis of the number of wine types consumed by residents of Tenerife is carried out, with an aim to observe which characteristics determine the exclusivity in its consumption, given the current context of increased competition in this sector. The specific characteristics of the considered variable allow the study to cover two aspects. The first is methodological, and is seen by the variety of models that may be considered in this case. This focus consists in comparing several possibilities which fit the type of count data involved. The second aspect is clearly empirical, and is based on the description of not only the most appropriate decision-making mechanism for the study but in the identification of those factors that explain the diversity in wine consumption.

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“…Since the parameter λ is the mean of the corresponding Poisson (λ) we call it a Poisson mean. Since the observed values are all positive, the ZTP distribution is sometimes called a positive Poisson (PP) distribution (Gurmu, 1991), see also David and Johnson (1952) and Cohen (1960). Since the zero-truncated distribution can be regarded as a conditional distribution under the condition that the count is restricted to positive values, the notation of conditional distribution is adopted in (2.1).…”

Section: Zero-truncated Poisson (Ztp) Distribution and Point Estimationmentioning

confidence: 99%

<b>ON INTERVAL ESTIMATION OF THE POISSON PARAMETER </b><b>IN A ZERO-TRUNCATED POISSON DISTRIBUTION </b>

Daidoji

Iwasaki²

2012

Journal of the Japanese Society of Computational Statistics

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When the research outcome is counts of a rare event, Poisson distribution is a first choice to describe the population distribution under study. However in some applications, the zero count would not be observed at all. In such cases the model to be fitted to the data is a zero-truncated Poisson (ZTP) distribution. This distribution is a special case of the more general zero-modified Poisson (ZMP) distribution family. This article discusses estimation procedures for the Poisson parameter of the ZTP model. In particular, performance of confidence intervals in terms of coverage probability is fully examined by Monte Carlo simulations. It is shown that the score-type interval behaves well but the Wald-type interval gives unsatisfactory results if the Poisson mean is small and/or sample size is not so large. A modification of the Wald-type interval is also given, and its performance is investigated by using simulations. The findings are also applicable to ZMP distributions.

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Tests for Detecting Overdispersion in the Positive Poisson Regression Model

Cited by 59 publications

References 24 publications

Determinants of Rural Farmers’ Adoption of Climate Change Adaptation Strategies: Evidence from the Amathole District Municipality, Eastern Cape Province, South Africa

Determinants of Rural Farmers’ Adoption of Climate Change Adaptation Strategies: Evidence from the Amathole District Municipality, Eastern Cape Province, South Africa

An analysis of count data models for the study of exclusivity in wine consumption

<b>ON INTERVAL ESTIMATION OF THE POISSON PARAMETER </b><b>IN A ZERO-TRUNCATED POISSON DISTRIBUTION </b>

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