STATISTICAL COMPUTING
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STATISTICAL COMPUTING

Statistical computing is the interface between statistics and computer science. It is the area of computational science specific to the mathematical science of statistics. This area is also developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education. The term ‘statistical computing’ may also be used to refer to computationally intensive statistical methods including resampling methods, Markov chain Monte Carlo methods, local regression, kernel density estimation, artificial neural networks and generalized additive models. Statistical Computing covers the interface between the statistical and computing sciences. First chapter focuses on the fully Bayesian algorithm for a conventional item response theory (IRT) model so that it can be implemented on a high performance parallel machine. Second chapter provides a characterization of the noisy algorithm, with a focus on fundamental stability properties like positive recurrence and geometric ergodicity. In third chapter, we introduce a new label-switching move and compute the marginal partition posterior to help to surmount these difficulties. Fourth chapter provides an application of non-reversible metropolis-hastings in a continuous setting by developing the necessary theory and applying the theory to Gaussian distributions in three and nine dimensions. Fifth chapter details on statistics and computing. Sixth chapter highlights on flexible parametric bootstrap for testing homogeneity against clustering and assessing the number of clusters. Seventh chapter details on Bayesian computation and eighth chapter considers the adaptive version of the Parallel Tempering algorithm. Tenth chapter introduces latent components of dependence, conditionally on which a new Bayes consistency is defined. A procedure is then proposed for the joint estimation of the expectation and variance parameters of the model. In eleventh chapter, we proposes a new nonparametric RO
Editora: MAGNUM PUBLISHING
ISBN: 9781682501115
ISBN13: 9781682501115
Edição: 1ª Edição - 2016
Número de Páginas: 226
Acabamento: HARDCOVER
por R$ 595,00 4x de R$ 148,75 sem juros