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作者：SRIRAM, TN; BASAWA, IV; HUGGINS, RM
作者单位：La Trobe University
摘要：For the critical and subcritical Galton-Watson processes with immigration, it is shown that if the data were collected according to an appropriate stopping rule, the natural sequential estimator of the offspring mean m is asymptotically normally distributed for each fixed m is-an-element-of (0, 1]. Furthermore, the sequential estimator is shown to be asymptotically normally distributed uniformly over a class of offspring distributions with m is-an=element-of (0, 1] bounded variance and satisfy...
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作者：GIJBELS, I; VERAVERBEKE, N
摘要：This paper deals with censored data estimation of a general class of von Mises-type functionals of the survival time distribution F. Conditions are given under which an almost sure asymptotic representation holds for the estimator, obtained by applying the same functional to F(n), the product-limit estimator of Kaplan and Meier.
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作者：BUCKLEW, JA; NEY, PE
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：The binary hypothesis testing problem of deciding between two Markov chains is formulated under memory constraints. The optimality criterion used is the exponential rate with which the probability of error approaches zero as the sample size tends to infinity. The optimal memory constrained test is shown to be the solution of a set of equations derived from suitable large deviation twistings of the transition matrices under the two hypotheses. A computational algorithm and some examples are giv...
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作者：GHOSH, BK; HUANG, WM
摘要：Bickel and Rosenblatt proposed a procedure for testing the goodness of fit of a specified density to observed data. The test statistic is based on the distance between the kernel density estimate and the hypothesized density, and it depends on a kernel K, a bandwidth b(n) and an arbitrary weight function a. We study the behavior of the asymptotic power of the test and show that a uniform kernel maximizes the power when a > 0.
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作者：BREIMAN, L
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作者：DATTA, S
摘要：Consider i.i.d. pairs (theta-i, X-i), i greater-than-or-equal-to l, where theta-1 has an unknown prior distribution omega and given theta-1, X-1 has distribution P theta-1. This setup aries naturally in the empirical Bayes problems. We put a probability (a hyperprior) on the space of all possible omega and consider the posterior mean omega of omega. We show that, under reasonable conditions, P omega = integral-P-theta d omega is consistent in L1. Under a identifiability assumption, this result...
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作者：CSORGO, M; GOMBAY, E; HORVATH, L
作者单位：University of Alberta; Utah System of Higher Education; University of Utah
摘要：A sequence of independent nonnegative random variables with common distribution function F is censored on the right by another sequence of independent identically distributed random variables. These two sequences are also assumed to be independent. We estimate the density function f of F by a sequence of kernel estimators f(n)(t) = (integral-infinity(infinity)K((t - x)/h(n)) dF(n)(x))/h(n), where h(n) is a sequence of numbers, K is kernel density function and F(n) is the product-limit estimato...
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作者：KONISHI, S
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：This paper considers the problem of constructing approximate confidence intervals for functional parameters in the nonparametric case. The approach based on transformation theory is applied to improve standard confidence intervals. The accelerated bias-corrected percentile interval introduced by Efron relies on the existence of a normalizing transformation with bias and skewness corrections, although calculation does not require explicit knowledge of its functional form. We formally construct ...
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作者：BARRON, AR; SHEU, CH
摘要：Probability density functions are estimated by the method of maximum likelihood in sequences of regular exponential families. This method is also familiar as entropy maximization subject to empirical constraints. The approximating families of log-densities that we consider are polynomials, splines and trigonometric series. Bounds on the relative entropy (Kullback-Leibler distance) between the true density and the estimator are obtained and rates of convergence are established for log-density f...
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作者：CHANG, IS; HSIUNG, CA
作者单位：Academia Sinica - Taiwan
摘要：This paper shows that Cox's partial score function is the projection of the score function on the (locally) E-ancillary subspace for the nuisance parameter (Small and McLeish). This is done by adapting the concepts of (locally) E-ancillarity and (locally) E-sufficiency for inference functions (McLeish and Small) to an extended Cox's regression model, where the baseline function is allowed to be a predictable process.
