Backward capacity-filtering for electronics Fabs

In electronics Fabs such as semiconductor Fabs and liquid crystal display (LCD) Fabs, which are capital-intensive, finite-capacity planning is critical to achieving full-capacity production and on-time production. However, existing finite-capacity planning methods do not adequately reflect the actual capacity profiles of an electronics Fab. In this paper, we propose a new Fab-level capacity-filtering procedure to generate finite-capacity plan: a backward capacity-filtering procedure for generating finite-capacity release plan. When developing the Fab-level filtering procedures, we use stage-level capacity-filtering algorithms as a key building block. In this study, we enhance the previous capacity-filtering algorithms proposed by one of the authors in order to facilitate the practical requirements of electronics Fabs. We apply the proposed capacity-filtering method to a modern LCD–TFT Fab in Korea. Performance analyses demonstrate that the proposed method is superior to existing methods.     

Objective Bayesian analysis based on upper record values from two-parameter Rayleigh distribution with partial information

In the life test, predicting higher failure times than the largest failure time of the observed is an important issue. Although the Rayleigh distribution is a suitable model for analyzing the lifetime of components that age rapidly over time because its failure rate function is an increasing linear function of time, the inference for a two-parameter Rayleigh distribution based on upper record values has not been addressed from the Bayesian perspective. This paper provides Bayesian analysis methods by proposing a noninformative prior distribution to analyze survival data, using a two-parameter Rayleigh distribution based on record values. In addition, we provide a pivotal quantity and an algorithm based on the pivotal quantity to predict the behavior of future survival records. We show that the proposed method is superior to the frequentist counterpart in terms of the mean-squared error and bias through Monte carlo simulations. For illustrative purposes, survival data on lung cancer patients are analyzed, and it is proved that the proposed model can be a good alternative when prior information is not given.     

Asymptotic expaxsioxs for the joint distribution of cirrelated hotellings t2 statlstics under normality

Let T² _i=z′_iS^?1z_i, i==,…k be correlated Hotelling's T² statistics under normality. where z=(z′_i,…,z′_k)′ and nS are independently distributed as N_kp((O,ρ?∑) and Wishart distribution W_p(∑, n), respectively. The purpose of this paper is to study the distribution function F(x₁,…,x_k) of (T² _i,…,T² _k) when n is large. First we derive an asymptotic expansion of the characteristic function of (T² _i,…,T² _k) up to the order n^?2. Next we give asymptotic expansions for (T² _i,…,T² _k) in two cases (i)ρ=I_k and (ii) k=2 by inverting the expanded characteristic function up to the orders n^?2 and n^?1, respectively. Our results can be applied to the distribution function of max (T² _i,…,T² _k) as a special case.     

Comment on “Constrained Optimization Approaches to Estimation of Structural Models”

We revisit the comparison of mathematical programming with equilibrium constraints (MPEC) and nested fixed point (NFXP) algorithms for estimating structural dynamic models by Su and Judd (2012). Their implementation of the nested fixed point algorithm used successive approximations to solve the inner fixed point problem (NFXP‐SA). We redo their comparison using the more efficient version of NFXP proposed by Rust (1987), which combines successive approximations and Newton–Kantorovich iterations to solve the fixed point problem (NFXP‐NK). We show that MPEC and NFXP are similar in speed and numerical performance when the more efficient NFXP‐NK variant is used.     

Reduced admissions for acute myocardial infarction associated with a public smoking ban: matched controlled study

There has been no research linking implementation of a public smoking ban and reduced incidence of acute myocardial infarction (AMI) among nonsmoking patients. An ex post facto matched control group study was conducted to determine whether there was a change in hospital admissions for AMI among nonsmoking patients after a public smoking ban was implemented in Monroe County compared with Delaware County, Indiana without such a ban. Poisson analysis was conducted for 44 months of hospital admissions. A significant drop occurred in the number of admissions among nonsmoking patients in Monroe County after the ban whereas a nonsignificant decrease in the number of admissions occurred in Delaware County. The changes in the number of smoking-patient admissions before and after the ban were not significant.     

The effects on the distributions of sample canonical correlations under nonnormality

In this paper, we study the effects of nonnormality on the distributions of sample canonical correlations when the population canonical correlations are simple. In order to achieve the purpose, we derive asymptotic expansion formulas for the distributions of a function of the canonical correlations as well as the individual canonical correlations under nonnormal populations. We particularly discuss the distribution of sample canonical correlations under the class of elliptical population. These expansions are given by using a perturbation method. Simulation results are also given.     

Cigarette Smoking Among Korean International College Students in the United States

Abstract

Objective and Participants: This study explored (1) the prevalence of cigarette smoking among South Korean international college students in the United States, (2) differences in smoking between on- and off-campus living arrangements, and (3) predictors of an increase in smoking over time in the United States Methods: An online survey was completed by 1,201 students at 52 4-year US universities (34% response rate). Results: The overall smoking prevalence was 43.5%. The smoking rate (29.0%) of female students was higher than that (4%) of female college students in South Korea. Sex, living place, living situation, length of stay as a student in the United States, home smoking rules, campus-wide tobacco-free policies, and levels of acculturative stress, anxiety, and depression were significantly associated with an increase in smoking (p < .05). Conclusions: Given the high smoking prevalence among the South Korean students on US college campuses, targeted prevention efforts for these students may be warranted.     

Estimation of the covariance matrix with two-step monotone missing data

Abstract

We suggest shrinkage based technique for estimating covariance matrix in the high-dimensional normal model with missing data. Our approach is based on the monotone missing scheme assumption, meaning that missing values patterns occur completely at random. Our asymptotic framework allows the dimensionality p grow to infinity together with the sample size, N, and extends the methodology of Ledoit and Wolf (2004) Ledoit, O., Wolf, M. (2004). A well-conditioned estimator for large dimensional covariance matrices. J. Multivariate Anal. 88:365–411.[Crossref], [Web of Science ®] , [Google Scholar] to the case of two-step monotone missing data. Two new shrinkage-type estimators are derived and their dominance properties over the Ledoit and Wolf (2004) Ledoit, O., Wolf, M. (2004). A well-conditioned estimator for large dimensional covariance matrices. J. Multivariate Anal. 88:365–411.[Crossref], [Web of Science ®] , [Google Scholar] estimator are shown under the expected quadratic loss. We perform a simulation study and conclude that the proposed estimators are successful for a range of missing data scenarios.