Optimization
Kenneth Lange(Author)
Springer (Publisher)
Published on 29. November 2010
Book
Paperback/Softback
XIII, 255 pages
978-1-4419-1910-6 (ISBN)
Description
Lange is a Springer author of other successful books.
This is the first book that emphasizes the applications of optimization to statistics.
The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics.
Reviews / Votes
From the reviews: "...An excellent, imaginative, and authoritative text on the difficult topic of modeling the problems of multivariate outcomes with different scaling levels, different units of analysis, and different study designs simultaneously." Biometrics, March 2005 "...As a textbook, Optimization does provide a valuable introduction to an important branch of applicable mathematics." Technometrics, August 2005 "...I found Optimization to be an extremely engaging textbook...the text is ideal for graduate students or researchers beginning research on optimization problems in statistics. There is little doubt that someone who worked through the text as part of a reading course or specialized graduate seminar would benefit greatly from the author's perspective..." Journal of the American Statistical Association, December 2005 "This is a book on optimization theory that includes some of the background mathematics necessary to understand ... . provides a good overview of graduate-level topics in optimization, including some of the supporting mathematics and some applications. ... The book has some every nice exercise sets to illuminate and extend the material covered in the textbook, as well as an extensive bibliography. ... a valuable introduction to an important branch of applicable mathematics." (Marvin H.J. Gruber, Technometrics, Vol. 47 (3), August, 2005)More details
Series
Edition
Softcover reprint of hardcover 1st ed. 2004
Language
English
Place of publication
NY
United States
Target group
Professional and scholarly
Research
Product notice
Paperback (trade)
Illustrations
black & white illustrations
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Thickness: 14 mm
Weight
850 gr
ISBN-13
978-1-4419-1910-6 (9781441919106)
DOI
10.1007/978-1-4757-4182-7
Schweitzer Classification
Other editions
Additional editions


Content
1 Elementary Optimization.- 2 The Seven C's of Analysis.- 3 Differentiation.- 4 Karush-Kuhn-Tucker Theory.- 5 Convexity.- 6 The MM Algorithm.- 7 The EM Algorithm.- 8 Newton's Method.- 9 Conjugate Gradient and Quasi-Newton.- 10 Analysis of Convergence.- 11 Convex Programming.- Appendix: The Normal Distribution.- A.1 Univariate Normal Random Variables.- A.2 Multivariate Normal Random Vectors.- References.