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作者：BOOTH, J; HALL, P; WOOD, A
摘要：Techniques are developed for bootstrap estimation of conditional distributions, with application to confidence intervals and hypothesis tests for one parameter, conditional on the value of an estimator of another. Both Monte Carlo and saddlepoint methods for approximating bootstrap distributions are considered, and empirical methods are suggested for implementing these techniques. For example, in the case of Monte Carlo methods, we suggest empirical techniques for selecting both the smoothing ...
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作者：CHEN, HF; LOH, WY
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：Bounds on the asymptotic relative efficiency (ARE) of the Box-Cox transformed two-sample t-test to the ordinary t-test are obtained under local alternatives. It is shown that the ARE is at least 1 for location-shift models. In the case of scale-shift models, a similar bound applies provided the limiting value of the estimated power transformation is greater than 1. If instead the Box-Cox transformed t-test is compared against the ordinary t-test applied to the log-transformed data, then the AR...
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作者：VANES, B
摘要：We consider the problem of bandwidth selection for kernel density estimators. Let H(n) denote the bandwidth computed by the least squares cross-validation method. Furthermore, let H(n)* and h(n)* denote the minimizers of the integrated squared error and the mean integrated squared error, respectively. The main theorem establishes asymptotic normality of H(n) - H(n)* and H(n) - h(n)*, for three classes of densities with comparable smoothness properties. Apart from densities satisfying the stand...
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作者：NAIMAN, DQ; WYNN, HP
作者单位：City St Georges, University of London
摘要：Improvements to the classical inclusion-exclusion identity are developed. There are two main results: an abstract combinatoric result and a concrete geometric result. In the abstract result conditions are given which guarantee the existence of a depth d + 1 identity or inequality for the indicator function of a union of a finite collection of events, that is, an expression which is a linear combination of indicator functions of at most (d + 1)-fold intersections of the events. Such an identity...
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作者：CHANG, YCI; MARTINSEK, AT
摘要：Let (X(i), Y(i)) be independent, identically distributed observations that satisfy a logistic regression model; that is, for each i, log[P(Y(i) = 1\X(i))/P(Y(i) = 0\X(i))] = X(i)(T)beta0, where Y(i) is-an-element-of {0, 1}, X(i) is-an-element-of (R)p and beta0 is-an-element-of R(p) is the unknown parameter vector of the model. The marginal distribution of the covariate vectors X(i) is assumed to be unknown. Sequential procedures for constructing fixed size and fixed proportional accuracy confi...
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作者：HEDAYAT, A
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作者：KUROTSCHKA, V; MULLER, C
摘要：P. J. Bickel's approach to and results on estimating the parameter vector beta of a conditionally contaminated linear regression model by asymptotically linear (AL) estimators beta* which have minimum trace of the asymptotic covariance matrix among all AL estimators with a given bound b on their asymptotic bias (MT-AL estimators with bias bound b) is here extended to conditionally contaminated general linear models and in particular for estimating arbitrary linear aspects phi(beta) = C-beta of...
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作者：OEHLERT, GW
摘要：Ordinary smoothing splines have an integrated mean squared error which is dominated by bias contributions at the boundaries. When the estimated function has additional derivatives, the boundary contribution to the bias affects the asymptotic rate of convergence unless the derivatives of the estimated function meet the natural boundary conditions. This paper introduces relaxed boundary smoothing splines and shows that they obtain the optimal asymptotic rate of convergence without conditions on ...
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作者：PERES, Y
作者单位：Hebrew University of Jerusalem
摘要：Given a sequence of independent, identically distributed random biased bits, von Neumann's simple procedure extracts independent unbiased bits. In this note we show that the number of unbiased bits produced by iterating this procedure is arbitrarily close to the entropy bound.
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作者：YU, QQ; PHADIA, E
作者单位：William Paterson University New Jersey
摘要：For the invariant decision problem of estimating a continuous distribution function with the Kolmogorov-Smirnov loss, it is proved that the best invariant estimator is minimax.
