Download PDF Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics)

[Free.ONaX] Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics)

[Free.ONaX] Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics)

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In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, on approximation and wavelet theory, and on the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is then presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Dynamical system - Wikipedia In mathematics a dynamical system is a system in which a function describes the time dependence of a point in a geometrical space Examples include the mathematical Mathematics Calendar - American Mathematical Society Mathematics Calendar Questions and answers regarding this page can be sent to mathcal@amsorg You can submit an entry to the Mathematics Calendar by filling out Stochastic process - Wikipedia The Wiener process is a stochastic process with stationary and independent increments that are normally distributed based on the size of the increments Andrei Nikolaevich Kolmogorov A N Kolmogorov Bibliography I General List of the main publications by A N Kolmogorov; Report to the mathematical circle on covering by squares (1921) [ihtiklibru] _ [ihtiklibru] _ : 10015 : 493 GB; KOLMOGOROV BOOKS Kolmogorov Books Selected Works of ANKolmogorov : Mathematics and Mechanics Volume 1 Edited by V M Tikhomirov Selected Works of ANKolmogorov : Probability Publications Page - Cambridge Machine Learning Group [ full BibTeX file] 2017 Jan-Peter Calliess Lipschitz optimisation for Lipschitz interpolation In 2017 American Control Conference (ACC 2017) Seattle WA USA Mathematical Modeling - Imperial College London Personal page of Professor Damiano Brigo at Imperial College London Dept of Mathematics Professor (Chair) Stochastic Analysis Group & co-Head of Mathematical Eurasc - New Members - eurascorg List of the new elected members to the European Academy of Sciences [ihtiklibru] _ [ihtiklibru] _ : 14292 : 573 GB; ; d:\_ihtiklibru\201203
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