作者:
Jonathan D. Cryer
/
Kung-Sik Chan 出版社: Springer 副标题: With Applications in R 出版年: 2010-11-17 页数: 508 定价: GBP 64.99 装帧: Hardcover ISBN: 9780387759586
This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of s...
This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.
作者简介
· · · · · ·
Jonathan D. Cryer 美国艾奥瓦大学统计与精算学系退休教授。他是美国统计学会会士，获得过艾奥瓦大学教学奖。除本书外，他还与人合著有《Statistics for Business: Data Analysis and Modeling, Second Edition》、《Minitab Handbook, Fifth Edition》、《Electronic Companion to Statistics》、《Electronic Companion to Business Statistics》等书，并发表了大量学术论文。
Kung-Sik Chan 美国艾奥瓦大学统计与精算学系教授。他是美国统计学会会士、数学统计学会会员，并且是国际统计学会推荐成员。他于1996年获得艾奥瓦大学系专家奖。除本书外，他还与人合著有《Chaos: A S...
Jonathan D. Cryer 美国艾奥瓦大学统计与精算学系退休教授。他是美国统计学会会士，获得过艾奥瓦大学教学奖。除本书外，他还与人合著有《Statistics for Business: Data Analysis and Modeling, Second Edition》、《Minitab Handbook, Fifth Edition》、《Electronic Companion to Statistics》、《Electronic Companion to Business Statistics》等书，并发表了大量学术论文。
Kung-Sik Chan 美国艾奥瓦大学统计与精算学系教授。他是美国统计学会会士、数学统计学会会员，并且是国际统计学会推荐成员。他于1996年获得艾奥瓦大学系专家奖。除本书外，他还与人合著有《Chaos: A Statistical Perspective》一书，并发表了大量学术论文。
原文摘录
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Prediction Using Cross-Correlation
As a simple example of cross-correlation, consider the problem of determining
possible leading or lagging relations between two series xt and yt.
If the model
yt = Axt− + wt
holds, the series xt is said to lead yt for
> 0 and is said to lag yt for
< 0.
Hence, the analysis of leading and lagging relations might be important
in predicting the value of yt from xt. Assuming, for convenience, that
xt and yt have zero means, and the noise wt is uncorrelated with the xt
series, the cross-covariance function can be computed as
γyx(h) = E(yt+hxt)
= AE(xt+h−xt) + E(wt+hxt)
= Aγx(h − l).
The cross-covariance function will look like the autocovariance of the
input series xt, with a peak on the positive side if xt leads yt and a peak
on the negative side if xt lag... (查看原文)
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机械工业出版社2011版
还没人写过短评呢
还没人写过短评呢