Author: Harvey NEWCOMB
Publisher:
ISBN:
Category :
Languages : en
Pages : 78
Book Description
Newcomb's Infant School Question Book ... Third edition
British Museum Catalogue of Printed Books
Catalogue of the Printed Books in the Library of the British Museum
The British Museum Catalogue of Printed Books, 1881-1900
Author: British Museum. Department of Printed Books
Publisher:
ISBN:
Category : English literature
Languages : en
Pages : 1160
Book Description
Publisher:
ISBN:
Category : English literature
Languages : en
Pages : 1160
Book Description
General Catalogue of Printed Books
Author: British Museum. Dept. of Printed Books
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 520
Book Description
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 520
Book Description
General Catalogue of Printed Books
Author: British Museum. Department of Printed Books
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 520
Book Description
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 520
Book Description
Newcomb's Wildflower Guide
Author: Lawrence Newcomb
Publisher: Little, Brown
ISBN: 9780316604420
Category : Nature
Languages : en
Pages : 490
Book Description
Line drawings face each description of the plant's basic structural features in this guide for the amateur wildflower sleuth
Publisher: Little, Brown
ISBN: 9780316604420
Category : Nature
Languages : en
Pages : 490
Book Description
Line drawings face each description of the plant's basic structural features in this guide for the amateur wildflower sleuth
General Catalogue of Printed Books to 1955
Author: British Museum. Dept. of Printed Books
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 1228
Book Description
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 1228
Book Description
Bayesian Data Analysis, Third Edition
Author: Andrew Gelman
Publisher: CRC Press
ISBN: 1439840954
Category : Mathematics
Languages : en
Pages : 677
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Publisher: CRC Press
ISBN: 1439840954
Category : Mathematics
Languages : en
Pages : 677
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.