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Stratified pair ranked set sampling

Stratified pair ranked set sampling is introduced and applied in estimating the population mean. Mathematical properties of the suggested estimator are treated. The estimator and its competitors are also compared through some numerical studies. Usefulness of the proposed design is illustrated using a cost analysis.     

Estimation in a random effects growth curve model

This paper considers estimation under the growth curve model of Potthoff and Roy (1964) with random effects. Estimation under a multivariate model is also considered. Estimation under incomplete data and estimation of random effects are also discussed. A numerical example of data on bulls is presented to illustrate these techniques.     

双重分层抽样中的校正估计

校正估计法已被大量运用于抽样调查中,它利用辅助信息构造的校正权重提高了对总体总值（或均值）的估计精度。本文提出了分层抽样中的校正组合比率估计量,并推广到分层双重抽样中。同时给出新估计量的近似方差表达式。最后利用计算机随机模拟验证较正估计量对估计精度的改进。     

Estimation of two ordered normal means when a covariance matrix is known

Estimation of two normal means with an order restriction is considered when a covariance matrix is known. It is shown that restricted maximum likelihood estimator (MLE) stochastically dominates both estimators proposed by Hwang and Peddada [Confidence interval estimation subject to order restrictions. Ann Statist. 1994;22(1):67–93] and Peddada et al. [Estimation of order-restricted means from correlated data. Biometrika. 2005;92:703–715]. The estimators are also compared under the Pitman nearness criterion and it is shown that the MLE is closer to ordered means than the other two estimators. Estimation of linear functions of ordered means is also considered and a necessary and sufficient condition on the coefficients is given for the MLE to dominate the other estimators in terms of mean squared error.     

Estimation in Degradation Models with Explanatory Variables

Influence of covariates on degradationis modelled. Models which include dependence of the intensityof the process of traumatic events on the degradation level arealso discussed. Estimation of reliability and degradation characteristicsfrom data with covariates is considered in dynamic environments.     

Estimation in two-parameter exponential distributions

Exponential distributions are used extensively in the field of life-testing. Estimation of parameters is revisited in two-parameter exponential distributions. A comparison study between the maximum likelihood method, the unbiased estimates which are linear functions of the maximum likelihood method, the method of product spacings, and the method of quantile estimates are presented. Finally, a simulation study is given to demonstrate the small sample properties     

Estimation of Short-Run and Long-Run Elasticities of Energy Demand From Panel Data Using Shrinkage Estimators

This article discusses the problem of obtaining short-run and long-run elasticities of energy demand for each of 49 states in the United States using data for 21 years. Estimation using the time series data by each state gave several wrong signs for the coefficients. Estimation using pooled data was not valid because the hypothesis of homogeneity of the coefficients was rejected. Shrinkage estimators gave more reasonable results. The article presents in a unified framework the classical, empirical Bayes, and Bayes approaches for deriving these estimators.     

Estimation and Simulation of the Riesz-Bessel Distribution

ABSTRACT

In this article, further properties of the Riesz-Bessel distribution are provided. These properties allow for the simulation of random variables from the Riesz-Bessel distribution. Estimation is addressed by nonlinear generalized least squares regression on the empirical characteristic function. The estimator is seen to approximate the maximum likelihood estimator. The distribution is illustrated with financial data.     

分层抽样估计方法新探

The paper puts forward two ways of thinking on stratified sampling estimation, the longitudinal auto-egression and multi-compound estimation method. The longitudinal auto-regression method probes into estimate of population mean based on the linear regression relationship between the means of the strata under investigation and ancillary characteristics. The multi-compound estimation method estimates the means of the strata separately by different methods and the population parameter is taken from these estimates. The paper further analyses conditions for the application of these methods; estimates and their error term; advantages and disadvantages and other problems of the two problems.     

Estimation of Population Means in Multivariate Stratified Random Sampling

In multivariate surveys where p (> 1) characteristics are defined on each unit of the population, the problem of allocation becomes complicated. In the present article, we propose a method to work out the compromise allocation in a multivariate stratified surveys. The problem is formulated as a Multiobjective Integer Nonlinear Programming Problem. Using the value function technique, the problem is converted into a single objective problem. A formula for continuous sample sizes is obtained using Lagrange Multipliers Technique (LMT) that can provide a near optimum solution in some cases. It may give an initial point for any integer nonlinear programing technique.