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Full-Text Articles in Probability
Em Estimation For Zero- And K-Inflated Poisson Regression Model, Monika Arora, N. Rao Chaganty
Em Estimation For Zero- And K-Inflated Poisson Regression Model, Monika Arora, N. Rao Chaganty
Mathematics & Statistics Faculty Publications
Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There are numerous articles that show how to fit Poisson and other models which account for the excessive zeros. However, in many situations, besides zero, the frequency of another count k tends to be higher in the data. The zero- and k-inflated Poisson distribution model (ZkIP) is appropriate in such situations The ZkIP distribution essentially is a mixture distribution of Poisson and degenerate distributions at points zero and k. In this article, we study the fundamental properties of this mixture distribution. Using stochastic representation, we …
Optimal Filtering Of An Advertising Production System With Deteriorating Items, Lakhdar Aggoun, Ali Benmerzouga, Lotfi Tadj
Optimal Filtering Of An Advertising Production System With Deteriorating Items, Lakhdar Aggoun, Ali Benmerzouga, Lotfi Tadj
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, we consider an integrated stochastic advertising-production system in the case of a duopoly. Two firms spend certain amounts to advertise some product. The expenses processes evolve according to the jumps of two homogeneous, finite-state Markov chains. We assume that the items in stock may be subject to deterioration and the deterioration parameter is assumed to be random.
Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang
Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang
Department of Statistics: Dissertations, Theses, and Student Work
This dissertation presents two statistical methodologies developed on multi-order Markov models. First, we introduce an alignment-free sequence comparison method, which represents a sequence using a multi-order transition matrix (MTM). The MTM contains information of multi-order dependencies and provides a comprehensive representation of the heterogeneous composition within a sequence. Based on the MTM, a distance measure is developed for pair-wise comparison of sequences. The new method is compared with the traditional maximum likelihood (ML) method, the complete composition vector (CCV) method and the improved version of the complete composition vector (ICCV) method using simulated sequences. We further illustrate the application of …