3期

最新文章

• INCREASING THE CONFIDENCE IN STUDENTS T-INTERVAL AI翻译
  作者：GOUTIS, C; CASELLA, G
  作者单位：Cornell University; Cornell University
  摘要：The usual confidence interval, based on Student's t distribution, has conditional confidence that is larger than the nominal confidence level. Although this fact is known, along with the fact that increased conditional confidence can be used to improve a confidence assertion, the confidence assertion of Student's t interval has never been critically examined. We do so here, and construct a confidence estimator that allows uniformly higher confidence in the interval and is closer (than 1 - alph...
• POLYA TREES AND RANDOM DISTRIBUTIONS AI翻译
  作者：MAULDIN, RD; SUDDERTH, WD; WILLIAMS, SC
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Utah System of Higher Education; Utah State University
  摘要：Trees of Polya urns are used to generate sequences of exchangeable random variables. By a theorem of de Finetti each such sequence is a mixture of independent, identically distributed variables and the mixing measure can be viewed as a prior on distribution functions. The collection of these Polya tree priors forms a convenient conjugate family which was mentioned by Ferguson and includes the Dirichlet processes of Ferguson. Unlike Dirichlet processes, Polya tree priors can assign probability ...
• TESTING GOODNESS-OF-FIT IN REGRESSION VIA ORDER SELECTION CRITERIA AI翻译
  作者：EUBANK, RL; HART, JD
  摘要：A new test is derived for the hypothesis that a regression function has a prescribed parametric form. Unlike many recent proposals this test does not depend on arbitrarily chosen smoothing parameters. In fact, the test statistic is itself a smoothing parameter which is selected to minimize an estimated risk function. The exact distribution of the test statistic is obtained when the error terms in the regression model are Gaussian, while the large sample distribution is derived for more general...
• ASYMPTOTICS FOR M-ESTIMATORS DEFINED BY CONVEX MINIMIZATION AI翻译
  作者：NIEMIRO, W
  摘要：We consider M-estimators defined by minimization of a convex criterion function, not necessarily smooth. Our asymptotic results generalize some of those concerning the LAD estimators. We establish a Bahadur-type strong approximation and bounds on the rate of convergence.
• MINIMUM HELLINGER-TYPE DISTANCE ESTIMATION FOR CENSORED-DATA AI翻译
  作者：YING, ZL
  摘要：A Hellinger-type distance for hazard rate functions is defined. It is used to obtain a class of minimum distance estimators for data that are subject to a possible right censorship. The corresponding score process is shown to be approximated by a martingale, which is exploited to obtain the asymptotic normality under considerably weaker conditions than those normally assumed for minimum Hellinger distance estimators. It is also shown that under the parametric assumption the estimators are asym...
• THE LEARNING COMPONENT OF DYNAMIC ALLOCATION INDEXES AI翻译
  作者：GITTINS, J; WANG, YG
  摘要：For a multiarmed bandit problem with exponential discounting the optimal allocation rule is defined by a dynamic allocation index defined for each arm on its space. The index for an arm is equal to the expected immediate reward from the arm, with an upward adjustment reflecting any uncertainty about the prospects of obtaining rewards from the arm, and the possibilities of resolving those uncertainties by selecting that arm. Thus the learning component of the index is defined to be the differen...
• BOOTSTRAP ESTIMATION OF CONDITIONAL DISTRIBUTIONS AI翻译
  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 ...
• BOUNDS ON ARES OF TESTS FOLLOWING BOX-COX-TRANSFORMATIONS AI翻译
  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...
• ASYMPTOTICS FOR LEAST-SQUARES CROSS-VALIDATION BANDWIDTHS IN NONSMOOTH CASES AI翻译
  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...
• STATISTICAL-ANALYSIS OF MULTIPLE ION CHANNEL DATA AI翻译
  作者：DABROWSKI, AR; MCDONALD, D
  摘要：Biological cell membranes contain molecular structures known as ion channels. The electrical activity of these channels regulates a number of cellular functions, such as heartbeat and neural transmission. Often the experimenter can only observe the combined current conducted through a cell patch containing an unknown number of ion channels, each channel of equal conductance. The observed current record is a step function with unit up or down steps occurring at random times. Based on such data,...