Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Parameter estimation on hurdle poisson regression model with censored data

    Access Status
    Fulltext not available
    Authors
    Greene, William
    Saffari, S.E.
    Adnan, R.
    Date
    2012
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Greene, W. and Saffari, S.E. and Adnan, R. 2012. Parameter estimation on hurdle poisson regression model with censored data. Jurnal Teknologi. 57 (1): pp. 189-198.
    Source Title
    Jurnal Teknologi
    Additional URLs
    http://www.jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/1533/1192
    ISSN
    2180-3722
    School
    School of Economics and Finance
    URI
    http://hdl.handle.net/20.500.11937/30109
    Collection
    • Curtin Research Publications
    Abstract

    A Poisson model typically is assumed for count data. In many cases, there are many zeros in the dependent variable and because of these many zeros, the mean and the variance values of the dependent variable are not the same as before. In fact, the variance value of the dependent variable will be much more than the mean value of the dependent variable and this is called over–dispersion. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, it is suggested to use a hurdle Poisson regression model to overcome over–dispersion problem. Furthermore, the response variable in such cases is censored for some values. In this paper, a censored hurdle Poisson regression model is introduced on count data with many zeros. In this model, we consider a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness–of–fit for the regression model is examined. We study the effects of right censoring on estimated parameters and their standard errors via an example.

    Related items

    Showing items related by title, author, creator and subject.

    • A poisson regression model for analysis of censored count data with excess zeroes
      Saffari, S.; Adnan, R.; Greene, William; Ahmad, M. (2013)
      Typically, a Poisson regression model is assumed for count data. In many cases, there are many zeros in the dependent variable, therefore the mean is not equal to the variance value of the dependent variable. Thus, we ...
    • Parameter estimation on hurdle poisson regression model with censored data
      Saffari, S.; Adnan, R.; Greene, William (2012)
      A Poisson model typically is assumed for count data. In many cases, there are many zeros in the dependent variable and because of these many zeros, the mean and the variance values of the dependent variable are not the ...
    • Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
      Greene, William; Adnan, R.; Saffari, S.E. (2013)
      Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable. Therefore, Poisson model is ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.