The Resource Optimization, Kenneth Lange
Optimization, Kenneth Lange
Resource Information
The item Optimization, Kenneth Lange represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 1 library branch.
Resource Information
The item Optimization, Kenneth Lange represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 1 library branch.
 Summary

 "This introduction to optimization attempts to strike a balance between presentation of mathematical theory and development of numerical algorithms. Building on students' skills in calculus and linear algebra, the text provides a rigorous exposition without undue abstraction. Its stress on convexity serves as bridge between linear and nonlinear programming and makes it possible to give a modern exposition of linear programming based on the interior point method rather than the simplex method. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics
 The intended audience also includes graduate students in applied mathematics, computational biology, computer science, economics, and physics as well as upper division undergraduate majors in mathematics who want to see rigorous mathematics combined with real applications."Jacket
 Language
 eng
 Extent
 xiii, 252 pages
 Contents

 5.
 Convexity
 6.
 The MM algorithm
 7.
 The EM algorithm
 8.
 Newton's method
 9.
 Conjugate gradient and quasiNewton
 1.
 10.
 Analysis of convergence
 11.
 Convex programming
 App.
 The normal distribution
 Elementary optimization
 2.
 The seven C's of analysis
 3.
 Differentiation
 4.
 KarushKuhnTucker theory
 Isbn
 9780387203324
 Label
 Optimization
 Title
 Optimization
 Statement of responsibility
 Kenneth Lange
 Language
 eng
 Summary

 "This introduction to optimization attempts to strike a balance between presentation of mathematical theory and development of numerical algorithms. Building on students' skills in calculus and linear algebra, the text provides a rigorous exposition without undue abstraction. Its stress on convexity serves as bridge between linear and nonlinear programming and makes it possible to give a modern exposition of linear programming based on the interior point method rather than the simplex method. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics
 The intended audience also includes graduate students in applied mathematics, computational biology, computer science, economics, and physics as well as upper division undergraduate majors in mathematics who want to see rigorous mathematics combined with real applications."Jacket
 Cataloging source
 DLC
 http://library.link/vocab/creatorName
 Lange, Kenneth
 Dewey number
 519.6
 Illustrations
 illustrations
 Index
 index present
 LC call number
 QA402.5
 LC item number
 .L34 2004
 Literary form
 non fiction
 Nature of contents
 bibliography
 Series statement
 Springer texts in statistics
 http://library.link/vocab/subjectName
 Mathematical optimization
 Label
 Optimization, Kenneth Lange
 Bibliography note
 Includes bibliographical references (pages [237]245) and index
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 5.
 Convexity
 6.
 The MM algorithm
 7.
 The EM algorithm
 8.
 Newton's method
 9.
 Conjugate gradient and quasiNewton
 1.
 10.
 Analysis of convergence
 11.
 Convex programming
 App.
 The normal distribution
 Elementary optimization
 2.
 The seven C's of analysis
 3.
 Differentiation
 4.
 KarushKuhnTucker theory
 Control code
 55502387
 Dimensions
 25 cm
 Extent
 xiii, 252 pages
 Isbn
 9780387203324
 Isbn Type
 (alk. paper)
 Lccn
 2004049158
 Media category
 unmediated
 Media MARC source
 rdamedia
 Media type code

 n
 Other physical details
 illustrations
 Label
 Optimization, Kenneth Lange
 Bibliography note
 Includes bibliographical references (pages [237]245) and index
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 5.
 Convexity
 6.
 The MM algorithm
 7.
 The EM algorithm
 8.
 Newton's method
 9.
 Conjugate gradient and quasiNewton
 1.
 10.
 Analysis of convergence
 11.
 Convex programming
 App.
 The normal distribution
 Elementary optimization
 2.
 The seven C's of analysis
 3.
 Differentiation
 4.
 KarushKuhnTucker theory
 Control code
 55502387
 Dimensions
 25 cm
 Extent
 xiii, 252 pages
 Isbn
 9780387203324
 Isbn Type
 (alk. paper)
 Lccn
 2004049158
 Media category
 unmediated
 Media MARC source
 rdamedia
 Media type code

 n
 Other physical details
 illustrations
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.library.missouri.edu/portal/OptimizationKennethLange/qIDlWDQEcNo/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/portal/OptimizationKennethLange/qIDlWDQEcNo/">Optimization, Kenneth Lange</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>