Comparing Generalized Linear Model of Count Data: Application towards Pteridophyta species

  • Authors

    • Mohd Asrul Affendi Abdullah
    • Siti Afiqah Muhamad Jamil
    • Faridah Kormin
    • Mustafa Mamat
    2018-08-17
    https://doi.org/10.14419/ijet.v7i3.28.20966
  • Poisson model, Zero-Inflated Poisson, Negative Binomial, Akaike Information Criterion (AIC).

  • Abstract

    Pteridophyta is known as “paku-pakis†in Malay and it is one the flora species that exists in ecological system. Besides, Pteridophyta is one of the species that need to be preserved. Either flora or fauna, both are very important to preserve the ecosystem and control the pollution. In order to observe the species, the fundamental unit of all diversity metrics is a count of specific individuals. In some consequences, the uncorrected counts of observed species often used in measuring the diversity which ignore detection together and established methods to be used to account for missed species. Analysis of count data is widely used in engineering, public health, epidemiology, medical studies, ecology and many research of interest. Rarity increases the number of locations with zero detection in excess of those expected under simple models of abundance. The aims of this study are to compare the Generalized Linear Model (GLiM) in the application of Pteridophyta species of count data.

     

     

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  • How to Cite

    Asrul Affendi Abdullah, M., Afiqah Muhamad Jamil, S., Kormin, F., & Mamat, M. (2018). Comparing Generalized Linear Model of Count Data: Application towards Pteridophyta species. International Journal of Engineering & Technology, 7(3.28), 58-63. https://doi.org/10.14419/ijet.v7i3.28.20966

    Received date: 2018-10-04

    Accepted date: 2018-10-04

    Published date: 2018-08-17