On use of symmetrical balanced incomplete block design in construction of sampling design realising pre-assigned sets of inclusion probabilities of first two orders.

Gupta, Nigam and Kumar (1982) proposed a sampling scheme using certain combinatorial properties of balanced incomplete block design (BIBD) which realises first order inclusion probabilities proportional to measure of size(IPPS). Here their results have been extended by presenting samplng schemes realising pre-assigned sets of inclusion probabilities of first two orders.     

Estimation of Mean of Sensitive Characteristics for Successive Sampling

In this article, new estimators for estimating the population mean of a sensitive variable using the concept of successive sampling over two occasions are proposed. The unbiasedness and the variance properties of the proposed estimators are investigated analytically as well as numerically.     

Recursive computation of inclusion probabilities in ranked-set sampling

We derive recursive algorithms for computing first-order and second-order inclusion probabilities for ranked-set sampling from a finite population. These algorithms make it practical to compute inclusion probabilities even for relatively large sample and population sizes. As an application, we use the inclusion probabilities to examine the performance of Horvitz-Thompson estimators under different varieties of balanced ranked-set sampling. We find that it is only for balanced Level 2 sampling that the Horvitz-Thompson estimator can be relied upon to outperform the simple random sampling mean estimator.     

基于贝叶斯推断的上证指数突变点研究

中国股市因法制建设、市场机制不完善以及投资者心理不成熟等原因,易受外界各种因素的影响而产生突变。本文引入基于贝叶斯推断的突变点判断方法,通过构造似然函数,同时利用先验信息和样本信息,并采用吉布斯抽样完成突变点位置的判断。此外,本文将突变点个数的判断问题作为模型的选择问题对待,采用后验优比进行抉择。引入该方法后,本文对我国上证指数序列的突变点个数及突变位置进行判断。研究发现,在1993年1月至2008年5月,上证指数存在四个突变点,分别为:1994年12月前后,2000年1月(或2001年7月)前后,2006年4月前后,2007年11月前后。     

Singular weighing designs and estimation of total weight

The problem of estimation of total weight of objects using a singular spring balance weighing design has been studied in this paper. A lower bound of the estimated total weight is obtained and some classes of designs attaining the lower bound are studied.     

Economic Design of VSI x-Bar Control Charts for Non Normally Distributed Data under Gamma (λ, 2) Failure Models

Numerous methods have been developed to calculate confidence intervals for the binomial proportion π. Boundedness and discreteness of the sample space imply that none achieves exactly the nominal α/2 left and right non coverage. We consider whether intervals calculated by a particular method tend to be located too close to, or too far out from, the center of symmetry of the support scale, 1/2. Interval location may be characterized by the balance of mesial and distal non coverage in a study evaluating coverage. A complementary approach, applicable to a calculated interval, is derived from the Box–Cox family of scale transformations.     

On the numerical behaviour of ARMA(P,Q) covariance determinants for various sample sizes

An algorithm for the covariance determinant of a stationary autoregressive-moving average model is considered. Some asymptotic properties of this determinant in the stationarity and invertibil-ity region of the process are studied numerically in simple special cases.     

Optimal Variable Sample Size and Sampling Interval MSE Chart Based on Improved Square Root Transformation

In the field of statistical process control (SPC), control charts for attributes are widely used to detect the out-of-control condition by checking the number of nondefective units or nondefective in a sample. In this article, we use the average time to signal (ATS) and the average number of observations to signal (ANOS) to evaluate the performance of the optimal variable sample size and sampling interval (VSSI) improved square root transformation (ISRT) mean square error (MSE) (VSSI_ ISRT_ MSE) control chart for attribute data. In addition, this control chart will be used to monitor: (1) the difference between the process mean and the target value, and (2) the process variance shifts. We found that the optimal VSSI_ ISRT_ MSE chart performs better than the specific VSSI, the optimal variable sampling interval (VSI), and the fixed parameters (FP) ISRT_MSE charts. An example is given to illustrate this new proposed approach.     

Asymmetric Volatility Models with Structural Breaks

This article develops an asymmetric volatility model that takes into consideration the structural breaks in the volatility process. Break points and other parameters of the model are estimated using MCMC and Gibbs sampling techniques. Models with different number of break points are compared using the Bayes factor and BIC. We provide a formal test and hence a new procedure for Bayes factor computation to choose between models with different number of breaks. The procedure is illustrated using simulated as well as real data sets. The analysis shows an evidence to the fact that the financial crisis in the market from the first week of September 2008 has caused a significant break in the structure of the return series of two major NYSE indices viz., S & P 500 and Dow Jones. Analysis of the USD/EURO exchange rate data also shows an evidence of structural break around the same time.     

Confidence sets as programming problems

Optimizing criteria for choosing a confidence set for a parameter are formulated as mathematical programming problems. The two optimizing criteria, probability of coverage and size of set, give rise to a pair of inverse programming problems. Several examples are worked out. The programming problems are then formulated to allow the incorporation of partial information about the parameter. By varying the family of prior distributions, a continuum of problems from the frequency approach to a Bayesian approach is obtained. Some examples are considered in which the family of priors contains more than one but not all prior distributions.