The Annals of Statistics

最新文章

• MULTIVARIATE ADAPTIVE REGRESSION SPLINES - DISCUSSION AI翻译
  作者：BREIMAN, L
• ON THE CONSISTENCY OF POSTERIOR MIXTURES AND ITS APPLICATIONS AI翻译
  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...
• CENTRAL LIMIT-THEOREMS FOR LP DISTANCES OF KERNEL ESTIMATORS OF DENSITIES UNDER RANDOM CENSORSHIP AI翻译
  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...
• NORMALIZING TRANSFORMATIONS AND BOOTSTRAP CONFIDENCE-INTERVALS AI翻译
  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 ...
• APPROXIMATION OF DENSITY-FUNCTIONS BY SEQUENCES OF EXPONENTIAL-FAMILIES AI翻译
  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...
• AN E-ANCILLARITY PROJECTION PROPERTY OF COXS PARTIAL SCORE FUNCTION AI翻译
  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.
• LARGE SAMPLE THEORY OF ESTIMATION IN BIASED SAMPLING REGRESSION-MODELS .1. AI翻译
  作者：BICKEL, PJ; RITOV, J
  作者单位：Hebrew University of Jerusalem; Nokia Corporation; Nokia Bell Labs; AT&T; New York University
  摘要：Biased sampling regression models were introduced by Jewell, generalizing the truncated regression model studied by Bhattacharya, Chernoff and Yang. If the independent variable takes on only a finite number of values (as does the stratum variable), we show: 1. That if the slope of the underlying regression model is assumed known, then the nonparametric maximum likelihood estimates of the distribution of the independent and dependent variables (a) can be calculated from ordinary M estimates; (b...
• BAHADUR REPRESENTATIONS FOR UNIFORM RESAMPLING AND IMPORTANCE RESAMPLING, WITH APPLICATIONS TO ASYMPTOTIC RELATIVE EFFICIENCY AI翻译
  作者：HALL, P
  摘要：We derive Bahadur-type representations for quantile estimates obtained from two different types of nonparametric bootstrap resampling-the commonly used uniform resampling method, where each sample value is drawn with the same probability, and importance resampling, where different sample values are assigned different resampling weights. These results are applied to obtain the relative efficiency of uniform resampling and importance resampling and to derive exact convergence rates, both weakly ...
• NONPARAMETRIC REGRESSION UNDER QUALITATIVE SMOOTHNESS ASSUMPTIONS AI翻译
  作者：MAMMEN, E
  摘要：We propose a new nonparametric regression estimate. In contrast to the traditional approach of considering regression functions whose m th derivatives lie in a ball in the L-infinity or L2 norm, we consider the class of functions whose (m - 1)st derivative consists of at most k monotone pieces. For many applications this class seems more natural than the classical ones. The least squares estimator of this class is studied. It is shown that the speed of convergence is as fast as in the classica...
• ESTIMATING A DISTRIBUTION FUNCTION WITH TRUNCATED AND CENSORED-DATA AI翻译
  作者：LAI, TL; YING, ZL
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
  摘要：A minor modification of the product-limit estimator is proposed for estimating a distribution function (not necessarily continuous) when the data are subject to either truncation or censoring, or to both, by independent but not necessarily identically distributed truncation-censoring variables. Making use of martingale integral representations and empirical process theory, uniform strong consistency of the estimator is established and weak convergence results are proved for the entire observab...