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Introduction to Computer-Intensive M...

Ebooks Corporation.

Introduction to Computer-Intensive Methods of Data Analysis in Biology.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to Computer-Intensive Methods of Data Analysis in Biology.
作者:	Roff, Derek A.
出版者:	Cambridge :Cambridge University Press,2006.
面頁冊數:	378 p.
標題:	Biology.
電子資源:	Click here to view book
ISBN:	9780511616785 (electronic bk.)

Introduction to Computer-Intensive Methods of Data Analysis in Biology.
Roff, Derek A.

Introduction to Computer-Intensive Methods of Data Analysis in Biology.[electronic resource]. - Cambridge :Cambridge University Press,2006. - 378 p.

Cover; Half-title; Title; Copyright; Contents; Preface; 1 An introduction to computer-intensive methods; 2 Maximum likelihood; 3 The jackknife; 4 The bootstrap; 5 Randomization and Monte Carlo methods; 6 Regression methods; 7 Bayesian methods; References; Appendix A: An overview of S-PLUS methods used in this book; Appendix B: Brief description of S-PLUS subroutines used in this book; Appendix C: S-PLUS codes cited in text; Appendix D: Solutions to exercises; Index

This graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding.

Electronic reproduction.

Available via World Wide Web.

Mode of access: World Wide Web.

ISBN: 9780511616785 (electronic bk.)Subjects--Topical Terms:

188667
Biology.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QH324.2 .R62 2006eb

Dewey Class. No.: 570.285

Introduction to Computer-Intensive Methods of Data Analysis in Biology.
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520 $a This graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding.
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