Titlebook: Applied Statistics and Data Science; Proceedings of Stati Yogendra P. Chaubey,Salim Lahmiri,Arusharka Sen Conference proceedings 2021 The E

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https://doi.org/10.1007/978-94-011-0611-5aphic and environmental characteristics at the health region level, was collected and published by Statistics Canada. The model performances were compared using information criteria, cross-validation, and residual analysis. The percentages of the immigrant population and graduates from health region

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Enzymatic Reactions in Organic Mediaalizing constant. An illustration in terms of a real data example is presented, where the computational algorithm is provided using . software. The resulting values are also checked using the Gibbs sampler using WinBUGS software.

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Modeling Obesity Rate with Spatial Auto-correlation: A Case Study,aphic and environmental characteristics at the health region level, was collected and published by Statistics Canada. The model performances were compared using information criteria, cross-validation, and residual analysis. The percentages of the immigrant population and graduates from health region

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Bayesian Inference for Inverse Gaussian Data with Emphasis on the Coefficient of Variation,alizing constant. An illustration in terms of a real data example is presented, where the computational algorithm is provided using . software. The resulting values are also checked using the Gibbs sampler using WinBUGS software.

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A Spatiotemporal Investigation of the Cod Stock in the Northern Gulf of St. Lawrence,presented. New specifications of the latent random field that try to capture the skewness of the cod data are proposed. This includes models for which the expected abundance at a site is infinite. The models proposed for cod abundance are compared using the likelihood ratio criterion. Model fitting

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Bayesian Inference for Inverse Gaussian Data with Emphasis on the Coefficient of Variation, and coefficient of variation (.). In the past literature, various parameterizations have been considered, some involving the coefficient of variation, where the prior distribution is assumed on the joint parameter (., .(.)), .(.) being some function. However, in some practical applications, the res