• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.11-21
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• 2007

The PDCA (Plan, Do, Check and Act) cycle is often used in the field of quality management. Recently, business environments have become more competitive, and the due time of products has shortened. In a short production run process, to increase efficiency of management, the necessity for distinguishing the PDCA design that starts with PLAN and the CAPD design that starts with CHECK has been clarified. Starting from Duncan (1956), there have been a number of papers dealing with the economic design of control charts from the viewpoint of production run. Some authors (Gibra, 1971; Ladany and Bedi, 1976; etc.) have studied the economic design for finite-length runs; other authors (Crowder, 1992; Del Castillo and Montgomery, 1996; etc.) have studied the economic design for short runs. However, neither the PDCA nor the CAPD design of control charts has been considered. In this paper, both the PDCA and CAPD designs of the $\bar{\x}$ chart are defined based on Del Castillo and Montgomery's design (1996), and their mathematical formulations are shown. Then from an economic viewpoint, the optimal values of the sample size per each sampling, control limits width, and the sampling interval of the two designs are studied. Finally, by numerically analyzing the relations between the key parameters and the total expected cost per unit time, the comparisons between the two designs are considered in detail.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.368-369
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• 1992

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.11
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• pp.1511-1514
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• 2012

Epistasis that may explain a large portion of the phenotypic variation for complex economic traits of animals has been ignored in many genetic association studies. A Baysian method was introduced to draw inferences about multilocus genotypic effects based on their marginal posterior distributions by a Gibbs sampler. A simulation study was conducted to provide statistical powers under various unbalanced designs by using this method. Data were simulated by combined designs of number of loci, within genotype variance, and sample size in unbalanced designs with or without null combined genotype cells. Mean empirical statistical power was estimated for testing posterior mean estimate of combined genotype effect. A practical example for obtaining empirical statistical power estimates with a given sample size was provided under unbalanced designs. The empirical statistical powers would be useful for determining an optimal design when interactive associations of multiple loci with complex phenotypes were examined.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.403-410
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• 2023

Two-Phase sampling, which was first introduced by Neyman (1938), has various applications in different forms. Variance estimation for two-phase sampling has been an important research topic because conventional variance estimators used in most softwares are not working. In this paper, we considered a variance estimation for two-phase sampling in which stratified two-stage cluster sampling designs are used in both phases. By defining a conditionally unbiased estimator of an approximate variance estimator, which is calculable when all elements in the first phase sample are observed, we propose an explicit form of variance estimator of the double expanded estimator for a two-phase sample. A small simulation study shows the proposed variance estimator has a negligible bias with small variance. The suggested variance estimator is also applicable to other linear estimators of the population total or mean if appropriate residuals are defined.

• Proceedings of the Korean Association for Survey Research Conference
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• 2002.11a
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• pp.255-274
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• 2002

We classify rotation sampling designs into two classes. The first class replaces sample units within the same rotation group while the second class replaces sample units between different rotation groups. The first class is specified by the three-way balanced design which is a multi-level version of previous balanced designs. We introduce an extended generalized composite estimator (EGCE) and derive its variance and mean squared error for each of the two classes of design, cooperating two types of correlations and three types of biases. Unbiased estimators are derived for difference between interview time biases, between recall time biases, and between rotation group biases. Using the variance and mean squared error, since any rotation design belongs to one of the two classes and the EGCE is a most general estimator for rotation design, we evaluate the efficiency of EGCE to simple weighted estimator and the effects of levels, design gaps, and rotation patterns on variance and mean squared error.

• Journal of the Korean Statistical Society
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• v.29 no.1
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• pp.45-62
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• 2000

Rotation design is a sampling technique to reduce response burden and to estimate the population characteristics varying in time. Park and Kim(1999) discussed a generation of one-level rotation design which is called as {{{{r_1^m ~-r_2^m-1}}}} design has more applicable form than existing before. In the structure of {{{{r_1^m ~-r_2^m-1}}}} design, we derive the exact variances of generalized composite estimators for level, change and aggregate level characteristics of interest, and optimal coefficients minimizing their variances. Finally numerical examples are shown by the efficiency of alternative designs relative to widely used 4-8-4 rotation design. This is continuous work of Part Ⅰ studied by Park and Kim(1999).

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.719-729
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• 2001

Overlap Maximization is a sampling technique to reduce survey costs and costs associated with the survey. It was first studied by Keyfitz(1951). Ernst(1998) presented a remarkable procedure for maximizing the overlap when the sampling units can be selected for two identical stratified designs simultaneously, But the approach involves mimicking the behaviour of nonlinear function by linear function and so it is less direct, even though the stratification problem for the overlap corresponds directly to the linear programming problem. furthermore, it uses the controlled selection algorithm that repeatedly needs zero-restricted controlled roundings, which are solutions of capacitated transportation problems. In this paper we suggest a comparatively simple procedure to use linear programming in order to maximize the overlap. We show how this procedure can be implemented practically.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1095-1102
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• 2011

The classical two-period, two-sequence crossover design is no longer sufficient to assess various demands in a bioequivalence study. For instance, to estimate the within-subject and between-subject variances of test and reference formulations separately, it is necessary to use a replicate design in which each subject receives at least the reference formulation in two periods. Several designs were studied to satisfy the demands. It is provided a unified Bayesian approach applicable to those study designs. The benefit of the method in the bioequivalence study is discussed.

• Acta Via Serica
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• v.7 no.2
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• pp.39-64
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• 2022

Ancient Iranians highly esteemed the horse and horse tacks, one of which is the jul (saddlecloth). It is a felt, sheepskin, or woven pad placed between the horse's back and saddle. The aim of this paper is to identify and categorize jul designs in the Sāsānian period. The research questions are about the variety of jul designs and how to categorize them. This is fundamental research and the method is descriptive and analytical. Neither a jul nor a saddle-cover remains from the Sāsānian period, therefore the statistical population includes all available items, such as metal and stone items and parget and plasterworks, in which juls are recognizable. Due to the scarcity of such items, all the available samples were studied; so the sampling method is a total enumeration. This is documentary research by means of note-taking and using reliable websites; the data has been analyzed qualitatively. The results show that jul designs were not diverse in the Sāsānian period. All-over designs were dominant. In terms of pattern types, these designs are classified into five groups, each of which has its own formal and aesthetic characteristics: all-over design with a four-petal flower pattern, allover design with a checkered pattern, all-over design with a spotted pattern, allover design with a tiger stripe pattern, and all-over design with a zigzag pattern.

• Journal of Korean Society for Quality Management
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• v.43 no.4
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• pp.471-488
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• 2015

Purpose: Double sampling $T^2$ chart is a useful tool for detecting a relatively small shift in process mean when the process is controlled by multiple variables. This paper finds the optimal design of the double sampling $T^2$ chart in both economical and statistical sense under Weibull failure model. Methods: The expected cost function is mathematically derived using recursive equation approach. The optimal designs are found using a genetic algorithm for numerical examples and compared to those of single sampling $T^2$ chart. Sensitivity analysis is performed to see the parameter effects. Results: The proposed design outperforms the optimal design of the single sampling $T^2$ chart in terms of the expected cost per unit time and Type-I error rate for all the numerical examples considered. Conclusion: Double sampling $T^2$ chart can be designed to satisfy both economic and statistical requirements under Weibull failure model and the resulting design is better than the single sampling counterpart.