4期

最新文章

• FIXED SIZE CONFIDENCE-REGIONS FOR PARAMETERS OF A LOGISTIC-REGRESSION MODEL AI翻译
  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...
• MINIMAXITY OF THE BEST INVARIANT ESTIMATOR OF A DISTRIBUTION FUNCTION UNDER THE KOLMOGOROV-SMIRNOV LOSS AI翻译
  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.
• DOMINANCE OF LIKELIHOOD RATIO TESTS UNDER CONE CONSTRAINTS AI翻译
  作者：MENENDEZ, JA; RUEDA, C; SALVADOR, B
  摘要：It is well known that anomalies are sometimes observed when using the likelihood ratio test (LRT) for testing restricted hypotheses in a normal model. This paper considers a general framework for these anomalies to occur. We provide a condition, that relates the null and the alternative hypotheses, under which the dominance of the LRT is obtained. Conditions are also given which guarantee the equivalence between the LRT and a simpler test. The situations of known and unknown variances are cons...
• ESTIMATING COEFFICIENT DISTRIBUTIONS IN RANDOM COEFFICIENT REGRESSIONS AI翻译
  作者：BERAN, R; HALL, P
  作者单位：Australian National University
  摘要：Random coefficient regression models are important in representing linear models with heteroscedastic errors and in unifying the study of classical fixed effects and random effects linear models. For prediction intervals and for bootstrapping in random coefficient regressions, it is necessary to estimate the distributions of the random coefficients consistently. We show that this is often possible and provide practical representative estimators of these distributions.
• INDETERMINATE PROBABILITIES ON FINITE SETS AI翻译
  作者：NAU, RF
  摘要：This paper presents a quasi-Bayesian model of subjective uncertainty in which beliefs which are represented by lower and upper probabilities qualified by numerical confidence weights. The representation is derived from a system of axioms of binary preferences which differs from standard axiom systems insofar as completeness is not assumed and transitivity is weakened. Confidence-weighted probabilities may be elicited through the acceptance of bets with limited stakes, a generalization of the o...
• BEST POSSIBLE CONSTANT FOR BANDWIDTH SELECTION AI翻译
  作者：FAN, JQ; MARRON, JS
  摘要：For the data based choice of the bandwidth of a kernel density estimator, several methods have recently been proposed which have a very fast asymptotic rate of convergence to the optimal bandwidth. In particular the relative rate of convergence is the square root of the sample size, which is known to be the best possible. The point of this paper is to show how semiparametric arguments can be employed to calculate the best possible constant coefficient, that is, an analog of the usual Fisher in...
• ASYMPTOTIC THEORY FOR NESTED CASE-CONTROL SAMPLING IN THE COX REGRESSION-MODEL AI翻译
  作者：GOLDSTEIN, L; LANGHOLZ, B
  作者单位：University of Southern California
  摘要：By providing a probabilistic model for nested case-control sampling in epidemiologic cohort studies, consistency and asymptotic normality of the maximum partial likelihood estimator of regression parameters in a Cox proportional hazards model can be derived using process and martingale theory as in Andersen and Gill. A general expression for the asymptotic variance is given and used to calculate asymptotic relative efficiencies relative to the full cohort variance in some important special cas...
• INVARIANCE PROPERTIES OF DENSITY RATIO PRIORS AI翻译
  作者：WASSERMAN, L
  摘要：Density ratio neighborhoods are classes of probabilities that are used in robust Bayesian inference. These classes are invariant under Bayesian updating and marginalization. This makes them computationally convenient in robust Bayesian inference. We show that this is the unique class of probabilities that has these invariance properties. Aside from its theoretical value, this result has computational implications as well.
• SOME RESULTS ON 2(N-K) FRACTIONAL FACTORIAL-DESIGNS AND SEARCH FOR MINIMUM ABERRATION DESIGNS AI翻译
  作者：CHEN, JH
  摘要：In this paper we find several interesting properties of 2n-k fractional factorial designs. An upper bound is given for the length of the longest word in the defining contrasts subgroup. We obtain minimum aberration 2n-k designs for k = 5 and any n. Furthermore, we give a method to test the equivalence of fractional factorial designs and prove that minimum aberration 2n-k designs for k less-than-or-equal-to 4 are unique.
• ELICITATION OF PRIOR DISTRIBUTIONS FOR VARIABLE-SELECTION PROBLEMS IN REGRESSION AI翻译
  作者：GARTHWAITE, PH; DICKEY, JM
  作者单位：University of Minnesota System; University of Minnesota Twin Cities
  摘要：This paper addresses the problem of quantifying expert opinion about a normal linear regression model when there is uncertainty as to which independent variables should be included in the model. Opinion is modeled as a mixture of natural conjugate prior distributions with each distribution in the mixture corresponding to a different subset of the independent variables. It is shown that for certain values of the independent variables, the predictive distribution of the dependent variable simpli...