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Basic Convergence Concepts and Theorems.- Metrics, Information Theory, Convergence, and Poisson Approximations.- More General Weak and Strong Laws and the Delta Theorem.- Transformations.- More General Clts.- Moment Convergence and Uniform Integrability.- Sample Percentiles and Order Statistics.- Sample Extremes.- Central Limit theorems for Dependent Sequences.- Central Limit Theorem for Markov Chains.- Accuracy of Clts.- Invariance Principles.- Edgeworth Expansions and Cumulants.- Saddlepoint Approximations.- U-Statistics.- Maximum Likelihood Estimates.- M Estimates.- the Trimmed Mean.- Multivariate Location Parameter and Multivariate Medians.- Bayes Procedures and Posterior Distributions.- Testing Problems.- Asymptotic Efficiency in Testing.- Some General Large Deviation Results.- Classical Nonparametrics.- Two-Sample Problems.- Goodness of Fit.- Chi-Square Tests for Goodness of Fit.- Goodness of Fit With Estimated Parameters.- The Bootstrap.- Jackknife.- Permutation Tests.- Density Estimation.- Mixture Models and Nonparametric Deconvolution.- High Dimensional Inference and False Discovery.
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Add Asymptotic Theory of Statistics and Probability, This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique in its detailed coverage of fundamental topics. It is, Asymptotic Theory of Statistics and Probability to the inventory that you are selling on WonderClubX
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Add Asymptotic Theory of Statistics and Probability, This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique in its detailed coverage of fundamental topics. It is, Asymptotic Theory of Statistics and Probability to your collection on WonderClub |