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作者：RITOV, Y; GILULA, Z
摘要：The RC model has been proposed as a model for ordered contingency tables. It involves parametric scores that are assigned to the rows and columns of the table so that these scores reflect the ordinality of the row and column categories. Efficient estimation of these parameters subject to order constraints remained an open problem mainly due to severe difficulties in computing these estimates and difficulties in deriving an appropriate asymptotic goodness-of-fit test. A nonstandard yet very sim...
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作者：FENECH, AP; HARVILLE, DA
作者单位：Iowa State University
摘要：We present a general procedure for obtaining an exact confidence set for the variance components in a mixed linear model. The procedure can be viewed as a generalization of the ANOVA method used with balanced models. Our procedure uses, as pivotal quantities, quadratic forms that are distributed independently as chi-squared variables. These quadratic forms are constructed with reference to spaces that are orthogonal with respect to the covariance matrix of the observation vector, which is a fu...
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作者：JONES, MC; MARRON, JS; PARK, BU
作者单位：Seoul National University (SNU); International Business Machines (IBM); IBM USA; University of North Carolina; University of North Carolina Chapel Hill
摘要：The asymptotically best bandwidth selectors for a kernel density estimator currently require the use of either unappealing higher order kernel pilot estimators or related Fourier transform methods. The point of this paper is to present a methodology which allows the fastest possible rate of convergence with the use of only nonnegative kernel estimators at all stages of the selection process. The essential idea is derived through careful study of factorizations of the pilot bandwidth in terms o...
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作者：ZHANG, P
摘要：In a nonparametric regression setup where the covariates are continuous, the problem of estimating the number of covariates will be discussed in this paper. The kernel method is used to estimate the regression function and the selection criterion is based on minimizing the cross-validation estimate of the mean squared prediction error. We consider choosing both the bandwidth and the number of covariates based on the data. Unlike the case of linear regression, it turns out that the selection is...
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作者：KEMPERMAN, JHB
摘要：We derive necessary and sufficient conditions in order that each mixture of a given family of probability densities have no more than s modal intervals, with special attention to ordinary unimodality and strong unimodality of such mixtures.
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作者：GOUTIS, C; CASELLA, G
作者单位：Cornell University
摘要：Confidence intervals for the variance of a normal distribution with unknown mean are constructed which improve upon the usual shortest interval based on the sample variance alone. These intervals have guaranteed coverage probability uniformly greater than a predetermined value 1 - alpha and have uniformly shorter length. Using information relating the size of the sample mean to that of the sample variance, we smoothly shift the usual minimum length interval closer to zero, simultaneously bring...
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作者：BARRON, AR
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作者：HEITJAN, DF; RUBIN, DB
作者单位：Harvard University
摘要：We present a general statistical model for data coarsening, which includes as special cases rounded, heaped, censored, partially categorized and missing data. Formally, with coarse data, observations are made not in the sample space of the random variable of interest, but rather in its power set. Grouping is a special case in which the degree of coarsening is known and nonstochastic. We establish simple conditions under which the possible stochastic nature of the coarsening mechanism can be ig...
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作者：STONE, CJ
摘要：Consider a Y-valued response variable having a density function f(.\x) that depends on an X-valued input variable x. It is assumed that X and Y are compact intervals and that f(.\.) is continuous and positive on X x Y. Let F(.\x) denote the distribution function of f(.\x) and let Q(.\x) denote its quantile function. A finite-parameter exponential family model based on tensor-product B-splines is constructed. Maximum likelihood estimation of the parameters of the model based on independent obse...
