Optimal design of repetitive group sampling plans for Weibull and gamma distributions with applications and comparison to the Birnbaum–Saunders distribution

In this paper, we propose a multiple deferred state repetitive group sampling plan which is a new sampling plan developed by incorporating the features of both multiple deferred state sampling plan and repetitive group sampling plan, for assuring Weibull or gamma distributed mean life of the products. The quality of the product is represented by the ratio of true mean life and specified mean life of the products. Two points on the operating characteristic curve approach is used to determine the optimal parameters of the proposed plan. The plan parameters are determined by formulating an optimization problem for various combinations of producer's risk and consumer's risk for both distributions. The sensitivity analysis of the proposed plan is discussed. The implementation of the proposed plan is explained using real-life data and simulated data. The proposed plan under Weibull distribution is compared with the existing sampling plans. The average sample number (ASN) of the proposed plan and failure probability of the product are obtained under Weibull, gamma and Birnbaum–Saunders distributions for a specified value of shape parameter and compared with each other. In addition, a comparative study is made between the ASN of the proposed plan under Weibull and gamma distributions.     

A comparative study of confidence intervals for negative binomial proportion

In this paper, we investigate four existing and three new confidence interval estimators for the negative binomial proportion (i.e., proportion under inverse/negative binomial sampling). An extensive and systematic comparative study among these confidence interval estimators through Monte Carlo simulations is presented. The performance of these confidence intervals are evaluated in terms of their coverage probabilities and expected interval widths. Our simulation studies suggest that the confidence interval estimator based on saddlepoint approximation is more appealing for large coverage levels (e.g., nominal level≤1% ) whereas the score confidence interval estimator is more desirable for those commonly used coverage levels (e.g., nominal level>1% ). We illustrate these confidence interval construction methods with a real data set from a maternal congenital heart disease study.     

Phase-II monitoring and diagnosing of multivariate categorical processes using generalized linear test-based control charts

In this paper, two control charts based on the generalized linear test (GLT) and contingency table are proposed for Phase-II monitoring of multivariate categorical processes. The performances of the proposed methods are compared with the exponentially weighted moving average-generalized likelihood ratio test (EWMA-GLRT) control chart proposed in the literature. The results show the better performance of the proposed control charts under moderate and large shifts. Moreover, a new scheme is proposed to identify the parameter responsible for an out-of-control signal. The performance of the proposed diagnosing procedure is evaluated through some simulation experiments.     

The economic design of multivariate binomial EWMA VSSI control charts

Since multi-attribute control charts have received little attention compared with multivariate variable control charts, this research is concerned with developing a new methodology to employ the multivariate exponentially weighted moving average (MEWMA) charts for m-attribute binomial processes; the attributes being the number of nonconforming items. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean shifts faster than the traditional MEWMA, an economic design of the VSSI MEWMA chart is proposed to obtain the optimum design parameters of the chart. The sample size, the sampling interval, and the warning/action limit coefficients are obtained using a genetic algorithm such that the expected total cost per hour is minimized. At the end, a sensitivity analysis has been carried out to investigate the effects of the cost and the model parameters on the solution of the economic design of the VSSI MEWMA chart.     

A股上市公司变相财务操纵对行业估值的影响

关于上市公司利润操控的相关研究主要是将净利润作为一个事关操控的敏感指标,但在监管与被监管双方努力的博弈下,其可被操纵的潜力已被充分挖掘。从实证角度关注上市公司财务操纵的其他可操作途径,其中就包括一些看似合理的变相财务操纵手段。按照2001年中国证监会公布的《上市公司行业分类指引》,把我国上市企业分为13个行业,对不同行业内企业2003—2013年部分主观可操控的财务指标与其所在行业的平均市盈率进行格兰杰因果检验和回归分析,结果表明,一些行业内企业的部分财务指标与其所在行业的平均市盈率存在领先与滞后关系,并且影响作用显著。     

Urinary Excretion of Chromium Following Ingestion of Chromite-Ore Processing Residues in Humans: Implications for Biomonitoring

Biomonitoring programs for urinary chromium (Cr) typically attempt to evaluate occupational exposure via the inhalation route. This study investigated whether Cr can be detected in the urine of people following the ingestion of soils that contain relatively high concentrations of chromium in chromite ore processing residue (COPR). To evaluate the reasonableness of using urinary monitoring to assess environmental exposure, six volunteers ingested 400 mg of soil/day (low-dose group), two others ingested 2.0 g of soil/day (high-dose group) for 3 consecutive days, and one person ingested a placebo on each of 3 days. The soil and COPR mixture contained concentrations of total chromium (Cr) and hexavalent chromium [Cr(VI)] of 103 ± 20 and 9.3 ± 3.8 mg/kg, respectively. Therefore, the low-dose group ingested 41 μg Cr/day [including 3.7 μg Cr(VI)] and the high-dose group ingested 206 μg Cr/day [including 18.6 μg Cr(VI)] on each of 3 consecutive days. All urine samples were collected and analyzed individually for total Cr on the day prior to dosing, during the 3 days of dosing, and up to the first void 48 h after the last dose. No significant increases in urinary Cr excretion were found when background excretion data were compared with data following each of the 3 days of dosing or in daily mean urine concentrations of the high- vs the low-dose groups. It appears that Cr present in a soil and COPR mixture at Cr doses up to 200 μg/day is not sufficiently bioavailable for biomonitoring of urine to be informative. These results are consistent with previously published findings suggesting that incidental exposure to dusts and soils containing comparable levels of Cr will not result in increased concentrations of Cr in urine.     

Communication in Statistics-Theory and methods improved GQL estimation method for the generalised BINMA(1) model

In a recent research, the quasi-likelihood estimation methodology was developed to estimate the regression effects in the Generalized BINMA(1) (GBINMA(1)) process. The method provides consistent parameter estimates but, in the intermediate computations, moment estimating equations were used to estimate the serial- and cross-correlation parameters. This procedure may not result optimal parameter estimates, in particular, for the regression effects. This paper provides an alternative simpler GBINMA(1) process based on multivariate thinning properties where the main effects are estimated via a robust generalized quasi-likelihood (GQL) estimation approach. The two techniques are compared through some simulation experiments. A real-life data application is studied.     

A general inversion theorem for cointegration

A generalization of the Granger and the Johansen Representation Theorems valid for any (possibly fractional) order of integration is presented. This Representation Theorem is based on inversion results that characterize the order of the pole and the coefficients of the Laurent series representation of the inverse of a matrix function around a singular point. Explicit expressions of the matrix coefficients of the (polynomial) cointegrating relations, of the Common Trends and of the Triangular representations are provided, either starting from the Moving Average or the Auto Regressive form. This contribution unifies different approaches in the literature and extends them to an arbitrary order of integration. The role of deterministic terms is discussed in detail.     

MSE performance of the weighted average estimators consisting of shrinkage estimators when each individual regression coefficient is estimated

In this paper, we analytically derive the exact formula for the mean squared error (MSE) of two weighted average (WA) estimators for each individual regression coefficient. Further, we execute numerical evaluations to investigate small sample properties of the WA estimators, and compare the MSE performance of the WA estimators with the other shrinkage estimators and the usual OLS estimator. Our numerical results show that (1) the WA estimators have smaller MSE than the other shrinkage estimators and the OLS estimator over a wide region of parameter space; (2) the range where the relative MSE of the WA estimator is smaller than that of the OLS estimator gets narrower as the number of explanatory variables k increases.