Analysis of Long-Tailed Count Data by Poisson Mixtures

2005 ◽  
Vol 34 (3) ◽  
pp. 557-573 ◽  
Author(s):  
Ramesh C. Gupta ◽  
S.H. Ong
Keyword(s):  
Count Data ◽  
Poisson Mixtures

Hierarchical Bayes Analysis of Rare Events Using High-Dispersion Poisson Mixtures

2008 ◽  
Author(s):  
Marc A. Maes ◽  
Markus Dann ◽  
Michael Havbro Faber
Keyword(s):  
Count Data ◽  
Rare Events ◽  
Extreme Values ◽  
Risk Estimation ◽  
Auxiliary Variable ◽  
Hierarchical Bayes ◽  
High Dispersion ◽  
Posterior Distributions ◽  
Traditional Use ◽  
Poisson Mixtures

Modeling the occurrence of rare events such as multiyear ice or iceberg encounters, ship collisions, and several types of accidental events is often challenging because considerable dispersion is found to be associated with discrete count data. This may be due to fluctuations in the processes generating the events, or they may arise because of a complicated mixture of causal events or there may be other unexplained discontinuities. In such cases, the traditional use of the Poisson distribution is inadequate, especially when the event frequency is subsequently used to formulate design criteria based on extreme values. In this paper, the use of discrete Poisson mixtures is suggested as opposed to the simple Poisson process and continuous Poisson mixtures. One objective is to ensure that the uncertainty regarding event occurrence is well represented in both the central and tail parts of count data. The analysis of discrete Poisson mixtures involves the estimation of the number k of mixture components, the k Poisson occurrence rates, and the k weights of the mixture. Until recently such an analysis was considered daunting at best. However, the analysis can be re-cast as an equivalent Hierarchical Bayes (HB) net using an auxiliary variable vector Z of variable dimension. A Markov Chain Monte Carlo analysis can then be used to obtain the posterior distributions of the dimensionality of the mixture, the mixture weights and the occurrence rates themselves. Also, posterior distributions can be found for iceberg collision risks and iceberg scour rates. The approach is illustrated for an iceberg risk estimation.

Regression Analysis of Count Data

1998 ◽  
Author(s):  
A. Colin Cameron ◽  
Pravin K. Trivedi
Keyword(s):  
Regression Analysis ◽  
Count Data

Analyzing discontinuities in longitudinal count data: A multilevel generalized linear mixed model.

2020 ◽  
Author(s):  
James L. Peugh ◽  
Sarah J. Beal ◽  
Meghan E. McGrady ◽  
Michael D. Toland ◽  
Constance Mara
Keyword(s):  
Count Data ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Longitudinal Count Data

Exploring Attendance at a Traditional Cultural Event: The Case of a Holy Week Celebration

2020 ◽  
Vol 24 (1) ◽  
pp. 153-168
Author(s):  
Víctor Lafuente ◽  
José Ángel Sanz ◽  
María Devesa
Keyword(s):  
Cultural Capital ◽  
Cultural Heritage ◽  
Count Data ◽  
Data Model ◽  
Social Aspects ◽  
Social Nature ◽  
The World ◽  
Local Residents ◽  
The City ◽  
Complex Expression

Holy Week is one of the most important traditions in many parts of the world and a complex expression of cultural heritage. The main goal of this article is to explore which factors determine participation in Holy Week celebrations in the city of Palencia (Spain), measured through the number of processions attended. For this purpose, an econometric count data model is used. Variables included in the model not only reflect participants' sociodemographic features but other factors reflecting cultural capital, accumulated experience, and social aspects of the event. A distinction is drawn between three types of participants: brotherhood members, local residents, and visitors, among whom a survey was conducted to collect the information required. A total of 248 surveys were carried out among brotherhood members, 209 among local residents, and 259 among visitors. The results confirm the religious and social nature of this event, especially in the case of local participants. However, in the case of visitors, participation also depends on aspects reflecting the celebration's cultural and tourist dimension—such as visiting other religious and cultural attractions—suggesting the existence of specific tourism linked to the event. All of this suggests the need to manage the event, ensuring a balance is struck between the various stakeholders' interests and developing a tourist strategy that prioritizes public-private cooperation.

scholarly journals Semiparametric estimation for count data through weighted distributions

2009 ◽  
Vol 139 (10) ◽  
pp. 3625-3638 ◽  
Author(s):  
C.C. Kokonendji ◽  
T. Senga Kiessé ◽  
N. Balakrishnan
Keyword(s):  
Count Data ◽  
Semiparametric Estimation ◽  
Weighted Distributions
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