Sequential Estimation of Expectations in the Presence of Trend2

A sequence of independent random variables {Z_n:n≥ 1} with unknown probability distributions is considered and the problem of estimating their expectations {M_n+1: n≥ 1} is examined. The estimation of M_n+1 is based on a finite set {z_k:1≤k≤n}, each z_k being an observed value of Z_k, 1 ≤k≤n, and also based on the assumption that {M_n:n≥ 1} follows an unknown trend of a specified form.     

Estimation of Population Mean in the Presence of Linear Trend

The present article deals with some methods for estimation of finite populations means in the presence of linear trend among the population values. As a result, we provided a strategy for the selection of sampling interval k for the case of circular systematic sampling, which ensures better estimator for the population mean compared to other choices of the sampling interval. This has been established based on empirical studies. Further we more, applied multiple random starts methods for selecting random samples for the case of linear systematic sampling and diagonal systematic sampling schemes. We also derived the explicit expressions for the variances and their estimates. The relative performances of simple random sampling, linear systematic sampling and diagonal systematic sampling schemes with single and multiple random starts are also assessed based on numerical examples.     

Some Remarks about Robust Estimation of the Scale Parameter in Weighted Models

Using Zieliński's (1977 Zieliński , R. ( 1977 ). Robustness: a quantitative approach . Bull. Acad. Polon. Sci., Ser. Sci. Math. Astronom. Phys. 25 : 1281 – 1286 . [Google Scholar]) concept of robustness, B?a?ej (2007 B?a?ej , P. ( 2007 ). Robust estimation of the scale and weighted distributions . Appl. Math. (Warsaw) 34 : 39 – 45 . [Google Scholar]) obtained the uniformly most bias-robust estimates (UMBREs) of the scale parameter for some statistical models, in a class of linear functions of order statistics. Violations of the models are generated by weight functions. In this article the UMBRE of the scale parameter, based on order statistics, a more general weighted model is derived. Extension of a result of B?a?ej (2007 B?a?ej , P. ( 2007 ). Robust estimation of the scale and weighted distributions . Appl. Math. (Warsaw) 34 : 39 – 45 . [Google Scholar]) is given.     

评《先秦·秦汉统计思想史》

莫曰达先生编著的《先秦·秦汉统计思想史》(中国统计出版社 2 0 0 1年 7月版 ) ,应是第一部详细论述我国古代统计思想发展历史的学术著作。进行中国古代统计思想史的研究 ,研究者除了必须具备现代统计学理论的专业学术训练 ,同时还要具备比较深厚的中国传统学术素养和比较扎实的历史、文学基础 ,这种学识构成上的难度 ,其实也就是造成这方面学术成果不多的原因。另一方面 ,中国古代没有出现过系统论述统计问题、统计学理论的专门著作 ,但这并不表示我们的祖先在其社会生活、生产过程中没有相应的统计实践和相应的关于统计的思考。问题在于 …     

对统计学科建设与发展的思考

对统计学科建设与发展的思考阿思奇近年来,我国统计学的研究取得了一定的进展,有些方面达到了世界先进水平,但统计理论研究工作还停留在表层,发掘和拓展仍嫌不足。从近几年在国家统计局立项的情况看。统计基本理论研究项目只占总数的２％;在统计科技进步奖的获奖项目...     

对《非市场服务产出核算理论与方法》评介

国民经济核算理论研究与统计实践中急需研究解决的重要问题之一是非市场服务产出核算的范围和非市场服务产出核算方法。东北财经大学蒋萍教授主持完成的国家社会科学基金项目《非市场服务产出核算理论与方法》(项目编号 0 1BTJ0 0 8)对国际上关于非市场服务产出核算的最新动态及其对中国的借鉴意义、非市场服务产出核算制度对整个国民经济总量估计会产生怎样的影响等 ,作了全面介绍和深入研究。我有幸被邀为该课题成果书写鉴定意见 ,因而有机会先人一步 ,细研结题报告 ① ,感到很有收获。为了推进国家国民经济核算制度的修订 ,准确评估国…     

Bounded Estimation in the Presence of Nuisance Parameters

The aim of this paper is to extend in a natural fashion the results on the treatment of nuisance parameters from the profile likelihood theory to the field of robust statistics. Similarly to what happens when there are no nuisance parameters, the attempt is to derive a bounded estimating function for a parameter of interest in the presence of nuisance parameters. The proposed method is based on a classical truncation argument of the theory of robustness applied to a generalized profile score function. By means of comparative studies, we show that this robust procedure for inference in the presence of a nuisance parameter can be used successfully in a parametric setting.     

《中国古代统计思想史》评介

莫曰达编写的《中国古代统计思想史》已由中国统计出版社正式出版。这是我国出版的第一部比较完整的古代统计思想史著作 ,填补了这门学科的空白。莫曰达同志 1991年曾与李惠村合作 ,写了一本《中国统计史》 ,书中也介绍了一些统计思想的代表人物 ,但遗漏很多。统计史包括统计活     

Some Remarks on Testing Overdispersion in Zero-Inflated Poisson and Binomial Regression Models

This note extends the score test statistics for overdispersion in Poisson and binomial regression models (Dean, 1992 Dean , C. B. ( 1992 ). Testing for overdispersion in Poisson and binomial regression models . J. Amer. Statist. Assoc. 87 : 451 – 457 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) to the zero-inflated models. Some general results are obtained, and examples illustrate the application of the extended results.     

The Estimation of Food Expenditures From Household Budget Data in the Presence of Bulk Purchases

The aim of this article is the estimation of annual food expenditures with limited information about bulk purchases with data from a Spanish household-budget survey for 1990—1991. Three alternatives are compared. The first, currently used for official purposes, does not use all the information. The second uses all the available information in a rough way. The third assumes a formal model for the unknown frequency of purchases. The three alternatives are compared by a regression model that should be homogeneous with respect to the dummy variables that represent the partial information of the groups and should show a distinct pattern of outliers under each alternative. Finally, we study the effect of the official and the best alternative on food inflation and inequality measures. We find that they lead to similar inflation rates but to different inequality estimates.     

Estimation and Prediction in the Presence of Spatial Confounding for Spatial Linear Models

In studies that produce data with spatial structure, it is common that covariates of interest vary spatially in addition to the error. Because of this, the error and covariate are often correlated. When this occurs, it is difficult to distinguish the covariate effect from residual spatial variation. In an i.i.d. normal error setting, it is well known that this type of correlation produces biased coefficient estimates, but predictions remain unbiased. In a spatial setting, recent studies have shown that coefficient estimates remain biased, but spatial prediction has not been addressed. The purpose of this paper is to provide a more detailed study of coefficient estimation from spatial models when covariate and error are correlated and then begin a formal study regarding spatial prediction. This is carried out by investigating properties of the generalized least squares estimator and the best linear unbiased predictor when a spatial random effect and a covariate are jointly modelled. Under this setup, we demonstrate that the mean squared prediction error is possibly reduced when covariate and error are correlated.     

Estimation of Bowley's Coefficient of Skewness in the Presence of Auxiliary Information

In this paper, we suggest regression-type estimators for estimating the Bowley's coefficient of skewness using auxiliary information. To the first degree of approximation, the bias and mean-squared error expressions of the regression-type estimators are obtained, and the regions under which these estimators are more efficient than the conventional estimator are also determined. Further, a general class of estimators of the Bowley's coefficient of skewness is defined along with its properties. A class of estimators based on estimated optimum values is also defined. It is shown to the first degree of approximations that the variance of the class of estimators based on estimated optimum values is the same as that of the minimum variance of the proposed class of estimators. A simulation study is carried out to demonstrate the performance of the proposed difference estimator over the usual estimator.     

Adaptive Isotonic Estimation of the Minimum Effective and Peak Doses in the Presence of Covariates

We consider a problem of estimating the minimum effective and peak doses in the presence of covariates. We propose a sequential strategy for subject assignment that includes an adaptive randomization component to balance the allocation to placebo and active doses with respect to covariates. We conclude that either adjusting for covariates in the model or balancing allocation with respect to covariates is required to avoid bias in the target dose estimation. We also compute optimal allocation to estimate the minimum effective and peak doses in discrete dose space using isotonic regression.     

Quantile Estimation in the Presence of Auxiliary Information under Negatively Associated Samples

In this article, we apply the empirical likelihood technique to propose a new class of quantile estimators in the presence of some auxiliary information under negatively associated samples. It is shown that the proposed quantile estimators are asymptotically normally distributed with smaller asymptotic variances than those of the usual quantile estimators. It is also shown that blocking technique is an useful tool in estimating asymptotic variance under negatively associated samples, which makes it possible to construct normal approximation based confidence intervals for quantiles.     

Estimation of Ratio of Two Finite-Population Means in the Presence of Non Response

It is well known that a ranked set sample under perfect ranking provides more information than an i.i.d. sample of the same size. Then it may be interesting to study how much information is lost due to imperfect ranking. In this article, we consider some ranking mechanisms and study the loss of the Fisher information according to the degree of imperfect ranking. Then we continue to discuss the optimal combination of the sample size and number of strata in terms of maximizing the Fisher information for the bivariate normal and exponential distributions.     

Estimation of the Mean of a Sensitive Variable in the Presence of Auxiliary Information

Sousa et al. (2010 Sousa , R. , Shabbir , J. , Real , P. C. , Gupta , S. ( 2010 ). Ratio estimation of the mean of a sensitive variable in the presence of auxiliary information . J. Statist. Theor. Prac. 4 ( 3 ): 495 – 507 .[Taylor & Francis Online] , [Google Scholar]) introduced a ratio estimator for the mean of a sensitive variable and showed that this estimator performs better than the ordinary mean estimator based on a randomized response technique (RRT). In this article, we introduce a regression estimator that performs better than the ratio estimator even for modest correlation between the primary and the auxiliary variables. The underlying assumption is that the primary variable is sensitive in nature but a non sensitive auxiliary variable exists that is positively correlated with the primary variable. Expressions for the Bias and MSE (Mean Square Error) are derived based on the first order of approximation. It is shown that the proposed regression estimator performs better than the ratio estimator and the ordinary RRT mean estimator (that does not utilize the auxiliary information). We also consider a generalized regression-cum-ratio estimator that has even smaller MSE. An extensive simulation study is presented to evaluate the performances of the proposed estimators in relation to other estimators in the study. The procedure is also applied to some financial data: purchase orders (a sensitive variable) and gross turnover (a non sensitive variable) in 2009 for a population of 5,336 companies in Portugal from a survey on Information and Communication Technologies (ICT) usage.     

Sequential Procedure For Fixed Accuracy Estimation of the Population Size in Recapture Sampling

A sequential procedure is constructed to provide a fixed‐accuracy estimator for the number of faults in a system. This paper focuses on the case when faults are homogeneous. However, the method can be adapted to other models by choosing a more robust estimator. The accuracy of the estimator depends on the failure intensity, the length of testing period and the total number of faults in the system. Simulations illustrate the performance of the proposed procedure. The method is applied to an information system failure dataset.     

我国通货膨胀的趋势分析——《通货膨胀趋势研究》课题系列之三

2002年下半年以来,针对我国经济运行中出现的投资过快增长和粮价上涨过猛的局面,国家推出了一系列宏观调控政策。目前,宏观调控初现成效,投资和信贷增速明显回落,粮食价格稳中趋降,居民消费价格总水平明显回落,上游生产资料价格快速上涨的势头也有明显缓解。但同时,在建投资规模依然偏大,且有继续反弹的危险;煤、电、油、运仍较紧张,主要生产资料价格还在高位运行;资金、土地和劳动力等基础性要素价格不断走高。这些均对我国未来价格走势形成上涨压力。在这种情况下,准确判断我国当前的价格形势和本轮通货膨胀的演变趋势,对于下一步合理…     

The Estimation and Inference of a Panel Cointegration Model with a Time Trend

This article investigates the asymptotic properties of coefficient estimators in the panel cointegration model with a time trend. We find that the bias of OLS estimator for the slope coefficient in the panel cointegration model with a time trend is distinct from that in the panel cointegration model without a time trend. Meanwhile, the variance of the limiting distribution for the slope coefficient is larger in the panel cointegration model with a time trend than without a time trend.