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作者：HASTIE, T; TIBSHIRANI, R; BUJA, A
作者单位：University of Toronto; University of Toronto; Telcordia Technologies
摘要：Fisher's linear discriminant analysis is a valuable tool for multigroup classification. With a large number of predictors, one can find a reduced number of discriminant coordinate functions that are ''optimal'' for separating the groups. With two such functions, one can produce a classification map that partitions the reduced space into regions that are identified with group membership, and the decision boundaries are linear. This article is about richer nonlinear classification schemes. Linea...
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作者：BURR, D
摘要：We study bootstrap confidence intervals for three types of parameters in Cox's proportional hazards model: the regression parameter, the survival function at fixed time points, and the median survival time at fixed values of a covariate. Several types of bootstrap confidence intervals are studied, and the type of interval is determined by two factors. One factor is the method of drawing the bootstrap sample. We consider three such methods: (1) ordinary resampling from the empirical cumulative ...
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作者：SOOFI, ES
摘要：The purpose of this article is to discuss the intricacies of quantifying information in some statistical problems. The aim is to develop a general appreciation for the meanings of information functions rather than their mathematical use. This theme integrates fundamental aspects of the contributions of Kullback, Lindley, and Jaynes and bridges chaos to probability modeling. A synopsis of information-theoretic statistics is presented in the form of a pyramid with Shannon at the vertex and a tri...
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作者：TJOSTHEIM, D; AUESTAD, BH
作者单位：Universitetet i Stavanger; University of California System; University of California San Diego
摘要：In this article we suggest a nonparametric procedure for selecting significant lags in the model description of a general nonlinear stationary time series. The procedure can be applied to both the conditional mean and the conditional variance and is valid for heteroscedastic series. The procedure is illustrated by simulations and sunspot data, lynx data, and blowfly data are analyzed. It is indicated that projectors can be used in conjunction with the procedure for selecting significant lags t...
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作者：TJOSTHEIM, D; AUESTAD, BH
作者单位：Universitetet i Stavanger; University of California System; University of California San Diego
摘要：We study the possibility of identifying general linear and nonlinear time series models using nonparametric methods. The kernel estimators of the conditional mean and variance are used as a basis, and the properties of these quantities as model indicators are briefly discussed. Some drawbacks are pointed out, and motivated by these we introduce projections as tools of identification. The projections are especially useful for additive modeling. Expressions for the asymptotic bias and variance a...
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作者：CROUX, C; ROUSSEEUW, PJ; HOSSJER, O
作者单位：University of Antwerp; Lund University
摘要：In this article we introduce a new type of positive-breakdown regression method, called a generalized S-estimator (or GS-estimator), based on the minimization of a generalized M-estimator of residual scale. We compare the class of GS-estimators with the usual S-estimators, including least median of squares. It turns out that GS-estimators attain a much higher efficiency than S-estimators, at the cost of a slightly increased worst-case bias. We investigate the breakdown point, the maxbias curve...
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作者：ONEILL, TJ
作者单位：Australian National University
摘要：The logistic regression classification method uses parameter estimates that are the solution of an estimating equation. This article derives a convenient expression for the bias of a vector estimator defined by estimating equations. The expression and the results of O'Neill are used to derive the bias and the error or misclassification rate of logistic regression classification in two examples where the assumed model for logistic regression does not hold. Logistic regression classification is ...
