computer age statistical inference algorithms evidence and data science institute of mathematical statistics monographs

Download Book Computer Age Statistical Inference Algorithms Evidence And Data Science Institute Of Mathematical Statistics Monographs in PDF format. You can Read Online Computer Age Statistical Inference Algorithms Evidence And Data Science Institute Of Mathematical Statistics Monographs here in PDF, EPUB, Mobi or Docx formats.

Computer Age Statistical Inference

Author : Bradley Efron
ISBN : 9781107149892
Genre : Business & Economics
File Size : 83. 39 MB
Format : PDF, Docs
Download : 703
Read : 674

Get This Book


Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.

Computer Age Statistical Inference

Author : Bradley Efron
ISBN : 9781108107952
Genre : Mathematics
File Size : 79. 92 MB
Format : PDF, ePub, Docs
Download : 706
Read : 1041

Get This Book


The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Computer Age Statistical Inference

Author : Bradley Efron. Trevor Hastie
ISBN : 1108105912
Genre :
File Size : 26. 33 MB
Format : PDF, ePub, Docs
Download : 819
Read : 891

Get This Book



Large Scale Inference

Author : Bradley Efron
ISBN : 9781139492133
Genre : Mathematics
File Size : 79. 60 MB
Format : PDF, ePub
Download : 536
Read : 1064

Get This Book


We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.

An Introduction To The Bootstrap

Author : Bradley Efron
ISBN : 0412042312
Genre : Mathematics
File Size : 21. 45 MB
Format : PDF, Docs
Download : 185
Read : 692

Get This Book


Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.

Inferential Models

Author : Ryan Martin
ISBN : 9781439886519
Genre : Mathematics
File Size : 74. 54 MB
Format : PDF
Download : 518
Read : 315

Get This Book


A New Approach to Sound Statistical Reasoning Inferential Models: Reasoning with Uncertainty introduces the authors’ recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The authors show how an IM produces meaningful prior-free probabilistic inference at a high level. The book covers the foundational motivations for this new IM approach, the basic theory behind its calibration properties, a number of important applications, and new directions for research. It discusses alternative, meaningful probabilistic interpretations of some common inferential summaries, such as p-values. It also constructs posterior probabilistic inferential summaries without a prior and Bayes’ formula and offers insight on the interesting and challenging problems of conditional and marginal inference. This book delves into statistical inference at a foundational level, addressing what the goals of statistical inference should be. It explores a new way of thinking compared to existing schools of thought on statistical inference and encourages you to think carefully about the correct approach to scientific inference.

Statistical Inference

Author : S.D. Silvey
ISBN : 9781351414500
Genre : Mathematics
File Size : 52. 79 MB
Format : PDF, Mobi
Download : 854
Read : 978

Get This Book


Statistics is a subject with a vast field of application, involving problems which vary widely in their character and complexity.However, in tackling these, we use a relatively small core of central ideas and methods. This book attempts to concentrateattention on these ideas: they are placed in a general settingand illustrated by relatively simple examples, avoidingwherever possible the extraneous difficulties of complicatedmathematical manipulation.In order to compress the central body of ideas into a smallvolume, it is necessary to assume a fair degree of mathematicalsophistication on the part of the reader, and the book is intendedfor students of mathematics who are already accustomed tothinking in rather general terms about spaces and functions

Analysis Of Multivariate And High Dimensional Data

Author : Inge Koch
ISBN : 9780521887939
Genre : Business & Economics
File Size : 43. 64 MB
Format : PDF, ePub, Docs
Download : 273
Read : 1003

Get This Book


This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.

Bootstrap Methods And Their Application

Author : A. C. Davison
ISBN : 0521574714
Genre : Computers
File Size : 81. 22 MB
Format : PDF
Download : 122
Read : 353

Get This Book


This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: http://statwww.epfl.ch/davison/BMA/

Empirical Bayes Methods

Author : J. S. Maritz
ISBN : 9781351140621
Genre : Business & Economics
File Size : 46. 71 MB
Format : PDF, Docs
Download : 878
Read : 902

Get This Book


Originally published in 1970; with a second edition in 1989. Empirical Bayes methods use some of the apparatus of the pure Bayes approach, but an actual prior distribution is assumed to generate the data sequence. It can be estimated thus producing empirical Bayes estimates or decision rules. In this second edition, details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. Chapters also focus on alternatives to the empirical Bayes approach and actual applications of empirical Bayes methods.

Top Download:

Best Books