Get Discriminant Analysis and Statistical Pattern Recognition PDF

By Geoffrey McLachlan

ISBN-10: 0471691151

ISBN-13: 9780471691150

The Wiley-Interscience Paperback sequence includes chosen books which were made extra obtainable to shoppers that allows you to raise worldwide attraction and common movement. With those new unabridged softcover volumes, Wiley hopes to increase the lives of those works through making them to be had to destiny generations of statisticians, mathematicians, and scientists."For either utilized and theoretical statisticians in addition to investigators operating within the many components during which proper use might be made from discriminant concepts, this monograph offers a contemporary, entire, and systematic account of discriminant research, with the point of interest at the more moderen advances within the field."–SciTech ebook News". . . a really helpful resource of data for any researcher operating in discriminant research and development recognition."–Computational StatisticsDiscriminant research and Statistical trend popularity offers a scientific account of the topic. whereas the point of interest is on sensible concerns, either theoretical and useful matters are explored. one of the advances lined are regularized discriminant research and bootstrap-based evaluation of the functionality of a sample-based discriminant rule, and extensions of discriminant research stimulated by way of difficulties in statistical photograph research. The accompanying bibliography comprises over 1,200 references.

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The Wiley-Interscience Paperback sequence comprises chosen books which have been made extra available to shoppers so that it will bring up international attraction and normal circulate. With those new unabridged softcover volumes, Wiley hopes to increase the lives of those works through making them to be had to destiny generations of statisticians, mathematicians, and scientists.

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Extra info for Discriminant Analysis and Statistical Pattern Recognition (Wiley Series in Probability and Statistics)

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And 8 is the vector consisting of the elements of 81,. ,8, known a priori to be distinct. For example, if the groupconditional distributions are assumed to be multivariate normal with means p1,. ,pgand of the distinct elements of C. Note that since the elements of the vector 7r of the mixing proportions Zj sum to one, one of them is redundant in 9,but we will not modify q accordingly, at least explicitly. However, in our statements about the distribution of any estimator of 9,it will be implicitly assumed that one of the mixing proportions has been deleted from ?!.

I=l We are following Hills (1966) here in referring to the eci(Fi;t)and ec(F;t ) as the conditional or actual error rates, and to the euj(F) and eu(F) as the unconditional or expected error rates. Before the introduction of his careful terminology for the various types of error rates, there had been a good deal of confusion in the literature; see the comment of Cochran (1966). 2 Relevance of Error Rates Concerning the relevance of error rates in discriminant analysis, for allocation problems, they play a major role in providing a measure of the global performance of a discriminant rule.

4. 2) must also be high. 2), called the predictive value of a positive test (PVP), may be small. Hence, the usefulness of a test is often evaluated in terms of the PVP and the PVN, where the latter denotes the predictive value of a negative test, defined by pr(Z1 = 1I r(x;t) = 1). 3) with a similar expression for the PVN. 3), the sensitivity and specificity of the test are abbreviated to ec22 and ecll, respectively. 3) that in order to evaluate the PVP and PVN of a test, the disease prevalence rate r 2 , as well as the sensitivity and specificity, must be assessed.

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Discriminant Analysis and Statistical Pattern Recognition (Wiley Series in Probability and Statistics) by Geoffrey McLachlan


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