On Comparison Of Estimates Of Dispersion Using Generalized Pitman Nearness Criterion

In this paper, estimates QP dispersion matrix and its functions are compared based on generalized Pitman nearness criterion, Various Iosa functions are considered for the purpose. Locally superior estimates are defined and obtained. Comparison of these estimates are made with other standard ones. It is snown that within certain classes, defined in the paper, these are the best estimatcrs ia the generalized Fitman nearness sense     

Bayesian Estimation of Survival Functions under Stochastic Precedence

When estimating the distributions of two random variables, X and Y, investigators often have prior information that Y tends to be bigger than X. To formalize this prior belief, one could potentially assume stochastic ordering between X and Y, which implies Pr(X < or = z) > or = Pr(Y < or = z) for all z in the domain of X and Y. Stochastic ordering is quite restrictive, though, and this article focuses instead on Bayesian estimation of the distribution functions of X and Y under the weaker stochastic precedence constraint, Pr(X < or = Y) > or = 0.5. We consider the case where both X and Y are categorical variables with common support and develop a Gibbs sampling algorithm for posterior computation. The method is then generalized to the case where X and Y are survival times. The proposed approach is illustrated using data on survival after tumor removal for patients with malignant melanoma.     

一类广义(2+1)维非自治长短波方程的整体光滑解的存在唯一性

利用先验估计和Galerkin方法,研究了非线性广义耗散(2+1)维非自治长短波方程在H4per(Ω)×H3per(Ω)上光滑解的整体存在唯一性.     

Construction of Simultaneous Confidence Intervals for Ratios of Means of Lognormal Distributions

For constructing simultaneous confidence intervals for ratios of means for lognormal distributions, two approaches using a two-step method of variance estimates recovery are proposed. The first approach proposes fiducial generalized confidence intervals (FGCIs) in the first step followed by the method of variance estimates recovery (MOVER) in the second step (FGCIs–MOVER). The second approach uses MOVER in the first and second steps (MOVER–MOVER). Performance of proposed approaches is compared with simultaneous fiducial generalized confidence intervals (SFGCIs). Monte Carlo simulation is used to evaluate the performance of these approaches in terms of coverage probability, average interval width, and time consumption.     

Estimating the Prevalence of Illegal Drug Use

A generic globally applicable integral equation allows the estimation of hidden drug use. Formulas for estimating the prevalence of drug use are provided for both the assumed and known latency period. Estimates of prevalence of opiate use in Ireland ranging from 7,955 [5,789, 10,122] to 11,986 [8,792, 15,181] with prevalence rates ranging from 2.7 [2.0, 3.5] per 1,000 to 4.1 [3.0, 5.2] were obtained. The model can be implemented by service providers and planners if numbers of first treatments for drug use and the latency period are known or assumed.     

Models for estimating discount rates for long-term health risks using labor market data

This article utilizes evidence from job choices involving fatality risks to estimate individual discount rates for adverse health outcomes. The study compares the results from five distinct models for estimating discount rates from labor market data. The estimated discount rates range from 1% to 14% with confidence intervals that usually include financial market rates for the same period. This result, and consistent findings of significant compensating differentials for fatality risk, provide strong support for life-cycle models of individual rationality in the choice of job risks. Discounted value-of-life estimates are also developed and compared to the crosssection estimates that are more prevalent in the literature.     

Estimating the number of clusters

Hartigan (1975) defines the number q of clusters in a d ‐variate statistical population as the number of connected components of the set {f > c}, where f denotes the underlying density function on R^d and c is a given constant. Some usual cluster algorithms treat q as an input which must be given in advance. The authors propose a method for estimating this parameter which is based on the computation of the number of connected components of an estimate of {f > c}. This set estimator is constructed as a union of balls with centres at an appropriate subsample which is selected via a nonparametric density estimator of f. The asymptotic behaviour of the proposed method is analyzed. A simulation study and an example with real data are also included.     

Estimating with percentile grouped and truncated date from a scale parameter distribution

Data which is grouped and truncated is considered. We are given numbers n₁<…<n_k=n and we observe X_ni ),i=1,…k, and the tottal number of observations available (N> n_k is unknown. If the underlying distribution has one unknown parameter θ which enters as a scale parameter, we examine the form of the equations for both conditional, unconditional and modified maximum likelihood estimators of θ and N and examine when these estimators will be finite, and unique. We also develop expressions for asymptotic bias and search for modified estimators which minimize the maximum asymptotic bias. These results are specialized tG the zxponential distribution. Methods of computing the solutions to the likelihood equatims are also discussed.     

Rank-based analysis of repeated measures block designs

A rank-based inference is developed for repeated measures balanced incomplete block and randomized complete block designs using a suitable dispersion function. Asymptotic distributions of rank estimators are developed after establishing approximate linearity of the gradient vector of the dispersion function. Unlike available nonparametric procedures for those designs, estimation and testing are tied together. Three different test statistics are developed for testing the linear hypotheses. Friedman's (1937) statistic and Durbin's (1951) statistic are particular cases of one of the three proposed statistics. An estimate of a scale parameter which appears in the ARE expression as well as as in the variences and covariances of the rank estimators is discussed.     

线性抛物型方程的窄四边形元逼近方法

讨论了一类发展方程——线性抛物型方程的窄四边形元逼近方法,导出了相应的半离散格式和全离散格式,并通过一些新的技巧,得到了相应的误差估计.