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The cosine geometric distribution with count data modeling.

Christophe ChesneauHassan S BakouchTassaddaq HussainBilal A Para
Published in: Journal of applied statistics (2020)
In this paper, a new two-parameter discrete distribution is introduced. It belongs to the family of the weighted geometric distribution (GD), with the feature of using a particular trigonometric weight. This configuration adds an oscillating property to the former GD which can be helpful in analyzing the data with over-dispersion, as developed in this study. First, we present the basic statistical properties of the new distribution, including the cumulative distribution function, hazard rate function and moment generating function. Estimation of the related model parameters is investigated using the maximum likelihood method. A simulation study is performed to illustrate the convergence of the estimators. Applications to two practical datasets are given to show that the new model performs at least as well as some competitors.
Keyphrases
  • magnetic resonance
  • big data
  • magnetic resonance imaging
  • mass spectrometry
  • weight loss
  • computed tomography
  • peripheral blood
  • network analysis
  • contrast enhanced