A summary of research into the use of symbolic computation applied to statistical inference problems, showing the potential of the subject to automate statistical calculation. The text begins with algorithms for undergraduate problems and moves on to more powerful tools and applications. Series: Oxford Statistical Science Series. Num Pages: 172 pages, line figures. BIC Classification: PBKS; PBT. Category: (P) Professional & Vocational. Dimension: 166 x 281 x 19. Weight in Grams: 422. . 2000. Hardback. . . . .

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Bibliographic Details

Title: Symbolic Computation for Statistical Inference
Publisher: Oxford University Press
Publication Date: 2000
Language: English
ISBN 10: 0198507054
ISBN 13: 9780198507055
Binding: Hardcover
Condition: New

About this title

Synopsis

Over recent years, developments in statistical computing have freed statisticians from the burden of calculation and have made possible new methods of analysis that previously would have been too difficult or time-consuming. Up till now these developments have been primarily in numerical computation and graphical display, but equal steps forward are now being made in the area of symbolic computing: the use of computer languages and procedures to manipulate expressions. This allows researchers to compute an algebraic expression, rather than evaluate the expression numerically over a given range. This book summarizes a decade of research into the use of symbolic computation applied to statistical inference problems. It shows the considerable potential of the subject to automate statistical calculation, leaving researchers free to concentrate on new concepts. Starting with the development of algorithms applied to standard undergraduate problems, the book then goes on to develop increasingly more powerful tools. Later chapters then discuss the application of these algorithms to different areas of statistical methodology.

About the Author

D. F. Andrews is at University of Toronto. J. E. Stafford is at University of Toronto.

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