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作者：MUROTA, K; TAKEUCHI, K
作者单位：University of Tokyo
摘要：The empirical characteristic function is effectively applied to test for the shape of distribution. The squared modulus of the studentized empirical characteristic function is suggested for testing the composite hypothesis that .mu. + .sigma. X is subject to a known distribution, for unknown constants .mu. and .sigma.. The studentized empirical characteristic function, if properly normalized, converges weakly to a complex Gaussian process. Asymptotic considerations and computer simulation reve...
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作者：SCHERVISH, MJ
摘要：The problem of classifying an observation X into 1 of k multivariate normal distributions is considered. When samples are used to estimate the population parameters, the probabilities of correct classification and the associated error rates are random variables. Asymptotic expansions for the expected values and variances of these random variables, in terms of the inverses of the sample sizes, are found. Simulations were performed to evaluate the expansions.
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作者：DAWID, AP
作者单位：City St Georges, University of London
摘要：A convenient notation for certain matrix-variate distributions is introduced and justified; by emphasis on important underlying parameters and the theory on which it is based, it eases greatly the task of manipulating such distributions. Important examples include the matrix-variate normal, t, F and beta, and the Wishart and inverse Wishart distributions. The theory is applied to compound matrix distributions and to Bayesian prediction in the multivariate linear model.
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作者：BLAESILD, P
摘要：The contours of equal density of the 2-dimensional hyperbolic distribution indicate that this distribution is capable of describing a very specific and simple form for departure from the 2-dimensional normal distribution. One of the classical examples of 2-dimensional data showing nonnormal variation in Johannsen''s bean data. After a discussion of elementary properties of the 2-dimensional hyperbolic distribution, the possibility of fitting this distribution to a set of data, obtained from Jo...
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作者：JEWELL, NP; RAAB, GM
作者单位：Princeton University; University of Edinburgh
摘要：Estimation of variances by pooling information from a large number of small samples [i.e., radioactive counts in immunoassay studies], when the means are nuisance parameters about which no assumptions or prior knowledge are available, is considered. When the variance is proportional to the square of the mean, a consistent estimator is obtained from a marginal likelihood. This method cannot be generalized to other variance functions. Integrated likelihood, modified likelihood and partial condit...
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作者：HOSKING, JRM
摘要：The family of autoregressive integrated moving-average processes, widely used in time series analysis, is generalized by permitting the degree of differencing to take fractional values. The fractional differencing operator is defined as an infinite binomial series expansion in powers of the backward-shift operator. Fractionally differenced processes exhibit long-term persistence and antipersistence; the dependence between observations a long time span apart decays much more slowly with time sp...
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作者：SCHOENFELD, D
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作者：BRESLOW, N
作者单位：University of Washington; University of Washington Seattle
摘要：The properties of 4 commonly used estimators of the odds ratio are studied under a large-sample scheme in which the number of 2 .times. 2 tables increases, but the possible marginal configurations remain fixed. Neither the unconditional maximum likelihood nor the empirical logit estimators converge to the true odds ratio; their asymptotic bias is computed for certain special cases of interest. The conditional maximum likelihood and Mantel-Haenszel estimators, which are consistent, have asympto...
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作者：SHIBATA, R
作者单位：Institute of Science Tokyo; Tokyo Institute of Technology
摘要：An asymptotically optimal selection of regression variables is proposed. The key assumption is that the number of control variables is infinite or increases with the sample size. Mallows'' Cp, Akaike''s FPE and AIC methods are all asymptotically equivalent to this method.
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作者：BINDER, DA
摘要：The amount of computation required for implementing the Bayesian cluster analysis suggested by Binder (1978) is often too large for exact results to be feasible. A general algorithm is proposed for approximating the similarity matrix and the resulting optimal partition. This algorithm is applied to artificial and to real data. For the real data, it appears that the algorithm is successful at identifying the optimal partitions as well as those units whose group membership is doubtful. [Data inc...
