Introduction to Variance Estimation

Author: Kirk Wolter

Publisher: Springer Science & Business Media

ISBN:

Category: Mathematics

Page: 427

View: 996

Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.

Introduction to Variance Estimation

Author: Kirk Wolter

Publisher: Springer Science & Business Media

ISBN:

Category: Mathematics

Page: 448

View: 660

Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.

Introduction to Natural Language Processing

Author: Jacob Eisenstein

Publisher: MIT Press

ISBN:

Category: Computers

Page: 536

View: 964

A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.

Introduction to Nonparametric Estimation

Author: Alexandre B. Tsybakov

Publisher: Springer Science & Business Media

ISBN:

Category: Mathematics

Page: 214

View: 717

Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.

An Introduction to the Analysis of Variance

Author: Richard S. Bogartz

Publisher: Praeger Pub Text

ISBN:

Category: Mathematics

Page: 565

View: 408

This book is for students taking a first-year graduate statistics course in Psychology and takes into account the diverse backgrounds of these students by providing basic review and through the careful introduction of material as it is needed.

Actes de la Session

Proceedings of the Session

Author: International Statistical Institute

Publisher:

ISBN:

Category: Statistics

Page:

View: 804

Multivariate Geostatistics

An Introduction with Applications

Author: Hans Wackernagel

Publisher: Springer Science & Business Media

ISBN:

Category: Science

Page: 293

View: 712

An introduction to geostatistics stressing the multivariate aspects for scientists, engineers and statisticians. The book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of three basic methods of multivariate analysis. Applications from very different areas of science, as well as exercises with solutions, are provided to help convey the general ideas. In this second edition, the chapters regarding normal kriging and cokriging have been restructured and the section on non-stationary geostatistics has been entirely rewritten.

Introduction to Geostatistics

Applications in Hydrogeology

Author: P. K. Kitanidis

Publisher: Cambridge University Press

ISBN:

Category: Science

Page: 249

View: 160

This presents practical techniques for interpolation and estimation problems when analysing data from field observations.

An Introduction to Optimal Estimation of Dynamical Systems

Author: J.L. Junkins

Publisher: Springer

ISBN:

Category: Mathematics

Page: 339

View: 313

This text 1s designed to introduce the fundamentals of esti mation to engineers, scientists, and applied mathematicians. The level of the presentation should be accessible to senior under graduates and should prove especially well-suited as a self study guide for practicing professionals. My primary motivation for writing this book 1s to make a significant contribution toward minimizing the painful process most newcomers must go through in digesting and applying the theory. Thus the treatment 1s intro ductory and essence-oriented rather than comprehensive. While some original material 1s included, the justification for this text lies not in the contribution of dramatic new theoretical re sults, but rather in the degree of success I believe that I have achieved in providing a source from which this material may be learned more efficiently than through study of an existing text or the rather diffuse literature. This work is the outgrowth of the author's mid-1960's en counter with the subject while motivated by practical problems aSSociated with space vehicle orbit determination and estimation of powered rocket trajectories. The text has evolved as lecture notes for short courses and seminars given to professionals at Pr>efaae various private laboratories and government agencies, and during the past six years, in conjunction with engineering courses taught at the University of Virginia. To motivate the reader's thinking, the structure of a typical estimation problem often assumes the following form: • Given a dynamical system, a mathematical model is hypothesized based upon the experience of the investigator.