Search results for: inference

Statistical Decision Rules and Optimal Inference

Author : N. N. Cencov
File Size : 30.97 MB
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None available in plain English.

Statistical Inference Based on the likelihood

Author : Adelchi Azzalini
File Size : 47.59 MB
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The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical techniques can be generated from a few key concepts, in particular the likelihood. Focusing on those methods, which have both a solid theoretical background and practical relevance, the author gives formal justification of the methods used and provides numerical examples with real data.

Bayesian Inference

Author : Javier Prieto Tejedor
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The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.

The Design Inference

Author : William A. Dembski
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This 1998 book breathes new life into classical design arguments, showing how incomplete undirected causes are for science.

Foundations of Inference in Natural Science

Author : J O Wisdom
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Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction and Part IV outlines the shape of this problem and its solution take if transformed by the present approach.

Secure Networked Inference with Unreliable Data Sources

Author : Aditya Vempaty
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The book presents theory and algorithms for secure networked inference in the presence of Byzantines. It derives fundamental limits of networked inference in the presence of Byzantine data and designs robust strategies to ensure reliable performance for several practical network architectures. In particular, it addresses inference (or learning) processes such as detection, estimation or classification, and parallel, hierarchical, and fully decentralized (peer-to-peer) system architectures. Furthermore, it discusses a number of new directions and heuristics to tackle the problem of design complexity in these practical network architectures for inference.

Statistical Inference and Probability

Author : John MacInnes
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An experienced author in the field of data analytics and statistics, John Macinnes has produced a straight-forward text that breaks down the complex topic of inferential statistics with accessible language and detailed examples. It covers a range of topics, including: · Probability and Sampling distributions · Inference and regression · Power, effect size and inverse probability Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.

Inductive Inference and Its Natural Ground

Author : Hilary Kornblith
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Hilary Kornblith presents an account of inductive inference that addresses both its metaphysical and epistemological aspects. He argues that inductive knowledge is possible by virtue of the fit between our innate psychological capacities and the causal structure of the world. Kornblith begins by developing an account of natural kinds that has its origins in John Locke's work on real and nominal essences. In Kornblith's view, a natural kind is a stable cluster of properties that are bound together in nature. The existence of such kinds serves as a natural ground of inductive inference.Kornblith then examines two features of human psychology that explain how knowledge of natural kinds is attained. First, our concepts are structured innately in a way that presupposes the existence of natural kinds. Second, our native inferential tendencies tend to provide us with accurate beliefs about the world when applied to environments that are populated by natural kinds.

Inference Principles for Biostatisticians

Author : Ian C. Marschner
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Designed for students training to become biostatisticians as well as practicing biostatisticians, Inference Principles for Biostatisticians presents the theoretical and conceptual foundations of biostatistics. It covers the theoretical underpinnings essential to understanding subsequent core methodologies in the field. Drawing on his extensive experience teaching graduate-level biostatistics courses and working in the pharmaceutical industry, the author explains the main principles of statistical inference with many examples and exercises. Extended examples illustrate key concepts in depth using a specific biostatistical context. In addition, the author uses simulation to reinforce the repeated sampling interpretation of numerous statistical concepts. Reducing the computational complexities, he provides simple R functions for conducting simulation studies. This text gives graduate students with diverse backgrounds across the health, medical, social, and mathematical sciences a solid, unified foundation in the principles of statistical inference. This groundwork will lead students to develop a thorough understanding of biostatistical methodology.

Diagrammatic Representation and Inference

Author : Tim Dwyer
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This book constitutes the refereed proceedings of the 8th International Conference on the Theory and Application of Diagrams, Diagrams 2014, held in Melbourne, VIC, Australia in July/August 2014. The 15 revised full papers and 9 short papers presented together with 6 posters were carefully reviewed and selected from 40 submissions. The papers have been organized in the following topical sections: diagram layout, diagram notations, diagramming tools, diagrams in education, empirical studies and logic and diagrams.