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最新文章

• On the bias in estimating genetic length and other quantities in simplex constrained models AI翻译
  作者：Cohen, A; Kemperman, JHB; Sackrowitz, H
  作者单位：Rutgers University System; Rutgers University New Brunswick
  摘要：The genetic distance between two loci on a chromosome is defined as the mean number of crossovers between the loci. The parameters of the crossover distribution are constrained by the parameters of the distribution of chiasmata. Ott (1996) derived the maximum likelihood estimator (MLE) of the parameters of the crossover distribution and the MLE of the mean. We demonstrate that the MLE of the mean is pointwise less than or equal to the empirical mean number of crossovers. It follows that the ML...
• Marginal models for categorical data AI翻译
  作者：Bergsma, WP; Rudas, T
  作者单位：Tilburg University; HUN-REN; HUN-REN Centre for Social Sciences; Institute for Sociology - HAS; Eotvos Lorand University; Central European University
  摘要：Statistical models defined by imposing restrictions on marginal distributions of contingency tables have received considerable attention recently. This paper introduces a general definition of marginal log-linear parameters and describes conditions for a marginal log-linear parameter to be a smooth parameterization of the distribution and to be variation independent. Statistical models defined by imposing affine restrictions on the marginal log-linear parameters are investigated. These models ...
• On weak base hypotheses and their implications for boosting regression and classification AI翻译
  作者：Jiang, WX
  作者单位：Northwestern University
  摘要：When studying the training error and the prediction error for boosting, it is often assumed that the hypotheses returned by the base learner are weakly accurate, or are able to beat a random guesser by a certain amount of difference. It has been an open question how much this difference can be. whether it will eventually disappear in the boosting process or be bounded by a positive amount. This question is crucial for the behavior of both the training error and the prediction error. In this pa...
• Spectral analysis for harmonizable processes AI翻译
  作者：Lii, KS; Rosenblatt, M
  作者单位：University of California System; University of California Riverside; University of California System; University of California San Diego
  摘要：Spectral estimation of nonstationary but harmonizable processes is considered. Given a single realization of the process, periodogram-like and consistent estimators are proposed for spectral mass estimation when the spectral support of the process consists of lines. Such a process can arise in signals of a moving source from array data or multipath signals with Doppler stretch from a single receiver. Such processes also include periodically correlated (or cyclostationary) and almost periodical...
• The screening effect in kriging AI翻译
  作者：Stein, ML
  作者单位：University of Chicago
  摘要：When predicting the value of a stationary random field at a location x in some region in which one has a large number of observations, it may be difficult to compute the optimal predictor. One simple way to reduce the computational burden is to base the predictor only on those observations nearest to x. As long as the number of observations used in the predictor is sufficiently large, one might generally expect the best predictor based on these observations to be nearly optimal relative to the...
• Confidence intervals for a binomial proportion and asymptotic expansions AI翻译
  作者：Brown, LD; Cai, TT; DasGupta, A
  作者单位：University of Pennsylvania; Purdue University System; Purdue University
  摘要：We address the classic problem of interval estimation of a binomial proportion. The Wald interval <(p)over cap> +/- (z)alpha/2(n-1/2)((p) over cap (1 - (p) over cap))(1/2) is currently in near universal use. We first show that the coverage properties of the Wald interval are persistently poor and defy virtually all conventional wisdom. We then proceed to a theoretical comparison of the standard interval and four additional alternative intervals by asymptotic expansions of their coverage probab...
• Randomized allocation with nonparametric estimation for a multi-armed bandit problem with covariates AI翻译
  作者：Yang, YH; Zhu, D
  作者单位：Iowa State University; Iowa State University
  摘要：We study a multi-armed bandit problem in a setting where covariates are available. We take a nonparametric approach to estimate the functional relationship between the response (reward) and the covariates. The estimated relationships and appropriate randomization are used to select a good arm to play for a greater expected reward. Randomization helps balance the tendency to trust the currently most promising arm with further exploration of other arms, It is shown that, with some familiar nonpa...
• Empirical margin distributions and bounding the generalization error of combined classifiers AI翻译
  作者：Koltchinskii, V; Panchenko, D
  作者单位：University of New Mexico
  摘要：We prove new probabilistic upper bounds on generalization error of complex classifiers that are combinations of simple classifiers. Such combinations could be implemented by neural networks or by voting methods of combining the classifiers, such as boosting and bagging. The bounds are in terms of the empirical distribution of the margin of the combined classifier. They are based on the methods of the theory of Gaussian and empirical processes (comparison inequalities, symmetrization method, co...
• Multiple hypotheses testing and expected number of type I errors AI翻译
  作者：Finner, H; Roters, M
  作者单位：University of Potsdam; Heinrich Heine University Dusseldorf
  摘要：The performance of multiple test procedures with respect to error control is an old issue. Assuming that all hypotheses are true we investigate the behavior of the expected number of type I errors (ENE) as a characteristic of certain multiple tests controlling the familywise error rate (FWER) or the false discovery rate (FDR) at a prespecified level. We derive explicit formulas for the distribution of the number of false rejections as well as for the ENE for single-step, step-down and step-up ...
• Asymptotic properties of adaptive designs for clinical trials with delayed response AI翻译
  作者：Bai, ZD; Hu, FF; Rosenberger, WF
  作者单位：National University of Singapore; University of Virginia; University System of Maryland; University of Maryland Baltimore County; University System of Maryland; University of Maryland Baltimore
  摘要：For adaptive clinical trials using a generalized Friedman's urn design, we derive the limiting distribution of the urn composition under staggered entry and delayed response. The stochastic delay mechanism is assumed to depend on both the treatment assigned and the patient's response. A very general setup is employed with K treatments and L responses. When L = K = 2, one example of a generalized Friedman's urn design is the randomized play-the-winner rule. An application of this rule occurred ...