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The term used for the estimation of the misclassification rate in the discriminant analysis. Number of techniques has been proposed for two-group situation, but the multiple-group situation has rarely been addressed. The easiest procedure is the resubstitution technique, in which the training data are classified using the estimated classification rule and proportion incorrectly placed used as the estimate of misclassification rate. This technique is known to have a large optimistic bias, but it has the benefit that it can be applied to the multigroup problems with no modification required. An alternative technique is the leave one out estimator, in which each of the observation in turn is removed from the data and the classification rule recomputed using remaining data. The proportion improperly classified by the procedure will have reduced bias compared to resubstitution technique. This method can also be implied to the multi group problem with no modification but it has the large amount of variance.
Length-biased data is a data which arise when the probability that an item is sampled is proportional to its own length. A main example of this situation occurs in the renewal the
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Regression through the origin : In some of the situations a relationship between the two variables estimated by the regression analysis is expected to pass by the origin because th
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how to find the PDF and CDF of a gamma random variable with given equation?
Thomas Economic Forecasting, Inc. and Harmon Econometrics have the same mean error in forecasting the stock market over the last ten years. However, the standard deviation for Thom
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what is the combine standard deviation height from the follwing
A law supposedly applicable to voting behaviour which has a history of several decades. It may be stated thus: Consider a two-party system and suppose that the representatives of t
Bartlett's test for variances : A test for equality of the variances of the number (k)of the populations. The test statistic can be given as follows where s square is an
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