Download Book Bootstrap in PDF format. You can Read Online Bootstrap here in PDF, EPUB, Mobi or Docx formats.

An Introduction To The Bootstrap

Author : Bradley Efron
ISBN : 0412042312
Genre : Mathematics
File Size : 36. 57 MB
Format : PDF, ePub, Docs
Download : 132
Read : 1055

Download Now Read Online

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.


Author : Jake Spurlock
ISBN : 9781449344603
Genre : Computers
File Size : 66. 27 MB
Format : PDF
Download : 234
Read : 159

Download Now Read Online

Discover how easy it is to design killer interfaces and responsive websites with the Bootstrap framework. This practical book gets you started building pages with Bootstrap’s HTML/CSS-based tools and design templates right away. You’ll also learn how to extend your app with interactive features, using its suite of jQuery plugins—often without writing a single line of code. Developed by Twitter and available free from GitHub, Bootstrap supports responsive design by dynamically adjusting your web page layout. With just a basic knowledge of HTML, CSS, and JavaScript, you can build apps that work equally well on desktop screens, smartphones, and tablets. This book shows you how. Become familiar with Bootstrap’s file structure, grid systems, and container layouts Learn HTML elements for typography, code, tables, forms, buttons, images, and icons Design interfaces and other web elements, such as navigation, breadcrumbs, and custom modal windows Use jQuery plugins for features such as revolving slideshows, tabbable interfaces, and dropdown menus Modify everything from column count to typography colors with the LESS stylesheet language

Bootstrap Methods And Their Application

Author : A. C. Davison
ISBN : 0521574714
Genre : Computers
File Size : 39. 57 MB
Format : PDF, ePub
Download : 741
Read : 546

Download Now Read Online

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:

The Jackknife And Bootstrap

Author : Jun Shao
ISBN : 9781461207955
Genre : Mathematics
File Size : 52. 86 MB
Format : PDF, ePub, Mobi
Download : 492
Read : 329

Download Now Read Online

The jackknife and bootstrap are the most popular data-resampling meth ods used in statistical analysis. The resampling methods replace theoreti cal derivations required in applying traditional methods (such as substitu tion and linearization) in statistical analysis by repeatedly resampling the original data and making inferences from the resamples. Because of the availability of inexpensive and fast computing, these computer-intensive methods have caught on very rapidly in recent years and are particularly appreciated by applied statisticians. The primary aims of this book are (1) to provide a systematic introduction to the theory of the jackknife, the bootstrap, and other resampling methods developed in the last twenty years; (2) to provide a guide for applied statisticians: practitioners often use (or misuse) the resampling methods in situations where no theoretical confirmation has been made; and (3) to stimulate the use of the jackknife and bootstrap and further devel opments of the resampling methods. The theoretical properties of the jackknife and bootstrap methods are studied in this book in an asymptotic framework. Theorems are illustrated by examples. Finite sample properties of the jackknife and bootstrap are mostly investigated by examples and/or empirical simulation studies. In addition to the theory for the jackknife and bootstrap methods in problems with independent and identically distributed (Li.d.) data, we try to cover, as much as we can, the applications of the jackknife and bootstrap in various complicated non-Li.d. data problems.

Exploring The Limits Of Bootstrap

Author : Raoul LePage
ISBN : 0471536318
Genre : Mathematics
File Size : 55. 16 MB
Format : PDF, Docs
Download : 701
Read : 460

Download Now Read Online

Explores the application of bootstrap to problems that place unusual demands on the method. The bootstrap method, introduced by Bradley Efron in 1973, is a nonparametric technique for inferring the distribution of a statistic derived from a sample. Most of the papers were presented at a special meeting sponsored by the Institute of Mathematical Statistics and the Interface Foundation in May, 1990.

The Jackknife The Bootstrap And Other Resampling Plans

Author : Bradley Efron
ISBN : 9780898711790
Genre : Computers
File Size : 52. 23 MB
Format : PDF, Docs
Download : 345
Read : 415

Download Now Read Online

This monograph connects the jackknife, the bootstrap, and many other related ideas into a unified exposition.

Bootstrap Techniques For Signal Processing

Author : Abdelhak M. Zoubir
ISBN : 1139452029
Genre : Technology & Engineering
File Size : 37. 28 MB
Format : PDF, Docs
Download : 642
Read : 769

Download Now Read Online

The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.

Top Download:

New Books