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Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series)
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D. F. Andrews 作者
Oxford University Press, USA
譯者
2000-08-24 出版日期
172 頁數
USD 195.00 價格
Hardcover
叢書系列
9780198507055 圖書編碼

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發表於2024-07-05

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 用戶評價

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Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 著者簡介

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 著者簡介

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Symbolic Computation for Statistical Inference (Oxford Statistical Science Series) 在線電子書 圖書描述

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, or in other words 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.

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