• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.

• Journal of the Korean Data and Information Science Society
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• 제14권1호
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• pp.55-65
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• 2003

In this study, we systemize the theoretical validity for applying unrelated question model to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the cost are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them.

• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• Asian-Australasian Journal of Animal Sciences
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• 제10권5호
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• pp.510-513
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• 1997

This study examined the effects of ignoring inbreeding depression on (co)variance components for weaning weight through the use of Monte Carlo simulation. Weaning weight is of particular interest as a trait for which additive direct and maternal genetic components exist and there then is the potential for a direct-maternal genetic covariance. Ignoring inbreeding depression in the analytical model (.8 kg reduction of phenotypic value per 1% inbreeding) led to biased estimates of all genetic (co) variance components, all estimates being larger than the true values of the parameters. In particular, a negative bias in the direct-maternal genetic covariance was observed in analyses that ignored inbreeding depression. A small spurious sire-by-year interaction variance was also observed.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.553-566
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• 2003

In many cases, the measurement error variances may be functions of the unknown true values or related covariates. This paper considers design-based estimators of the parameters of these variance functions based on the within-unit sample variances. This paper devotes to: (1) define an error scale factor $\delta$; (2) develop estimators of the parameters of the linear measurement error variance function of the true values under large-sample and small-error conditions; (3) use propensity methods to adjust survey weights to account for possible selection effects at the replicate level. The proposed methods are applied to medical examination data from the U.S. Third National Health and Nutrition Examination Survey (NHANES III).

• Communications for Statistical Applications and Methods
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• 제6권2호
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• pp.487-500
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• 1999

We propose a class of hierarchical Bayes estimators of the error variance under the relative squared error loss in balanced fixed-effects two-way analysis of variance models. Also we provide analytic expressions for the risk improvement of the hierarchical Bayes estimators over multiples of the error sum of squares. Using these expressions we identify a subclass of the hierarchical Bayes estimators each member of which dominates the best multiple of the error sum of squares which is known to be minimax. Numerical values of the percentage risk improvement are given in some special cases.

• 산업경영시스템학회지
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• 제23권61호
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• pp.89-98
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• 2000

For statistical process control, the process data are collected by the measurement system. But, the measurement system may have instrument error or/and operator error. In the measured values of products, the total observed variance consists of process variance and variance due to error of measurement system. In this paper, we design more practical T-s control chart considering estimated measurement error The effects of measurement error on the expected total cost and design parameters are investigated.

• Asian-Australasian Journal of Animal Sciences
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• 제23권3호
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• pp.302-307
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• 2010

The present study aimed to investigate the effects of maternal factors on body weight at hatching (day-old) and at six weeks of age in a commercial broiler line. A total of 6,765 records on body weight at day-old (BWTDO) and 115,421 records on body weight at six weeks of age (BWT6W), originated from a commercial broiler line during 14 generations, were used to estimate genetic parameters related to the effects of maternal traits on body weight of chicks immediately after hatch or six weeks thereafter. The data were analyzed using restricted maximum likelihood procedure (REML) and an animal model with DFREML software. Direct heritability ($h^{2}{_a}$), maternal heritability ($h^{2}{_m}$), and maternal environmental variance as the proportions of phenotypic variance ($c^{2}$) for body weight at day-old were estimated to be 0.050, 0.351, and 0.173, respectively. The respective estimated values for body weight at six weeks of age were 0.340, 0.022, and 0.030. The correlation coefficient between direct and maternal genetic effects for six-week-old body weight was found to be -0.335. Covariance components and genetic correlations were estimated using a bivariate analysis based on the best model determined by a univariate analysis. Between weights at hatching and at six week-old, the values of -0.07, 0.53 and 0.47 were found for the direct additive genetic variance, maternal additive genetic variance and permanent maternal environmental variance, respectively. The estimated correlation between direct additive genetic effect influencing weight at hatch and direct additive maternal effect affecting weight at six weeks of age was -0.21, whereas the correlation value of 0.15 was estimated between direct additive maternal effect influencing weight at hatch and direct additive genetic effect affecting weight at six-week-old. From the present findings, it can be concluded that the maternal additive genetic effect observed for weight at six weeks of age might be a factor transferred from genes influencing weight at hatch to weight at six-week-old.

• 복식문화연구
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• 제12권3호
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• pp.468-484
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• 2004

The purposes of this study were (1) to segment female college students' apparel shoppers into unique apparel buying decision-making style groups; and (2) to profile for each segment in terms of personal characteristics (material values, change seeking tendency and prestige sensitivity) and fashion information sources. Data were collected through questionnaires from convenient sample of 290 female college students. As a result of cluster analysis and univariate analysis of variance, distinctive consumer decision-making style groups of consumers were identified; Value-maximizing Recreational Shoppers, Brand-Maximizing Emotional Shoppers, and Apathetic Shoppers. These three groups were compared as to the effect of personal characteristics variables and fashion information sources through univariate analysis of variance and chi-square statistics. The result showed that personal characteristics (material values, change seeking tendency and prestige sensitivity) and fashion-information sources do influence the consumer decision-making styles and that these three groups were unique in their decision-making characteristics showing that consumer decision-making styles can be a good segmentation base for apparel market.

• 한국조경학회지
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• 제13권2호
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• pp.37-70
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• 1985

The purpose of this study is to present objective basic data for environmental design by the quantitative analysis of visual quality emboded in physical environment. For this, as for the front garden of high schools, the spatial image was measured by the S.D. Scale Method, Factor Analysis was proceeded by the principal component analysis and the visual preference was investigated by the Paired Comparision Method. The scale values of plain and unpleasant road surface and external appearance of buildings, which are related to emotions of simpleness fell from straightness and stability, were found to be high. But, except for the road surface of Kyunggi High School, scale values of variables explaining the variation of the quality of materials, level of floor and rythm were generally low. For all green spaces, scale values of variables explaining the degree of pleasantness was found to be generally high. And, those explaining tidiness and characteristics of green spaces were not in the same tendency. But, the green spaces of Youngdong High school can be considered to the space with plenty of visual absorption uniqueness were high. As for the correlation between variables, variables for green spaces(12 and 26) and those for overall view of front garden( 1 and 4) revealed high positive correlation. Also, "order - disorder" and "convenient- incovenient" included in road surface variable can be regarded to have the same meaning since the correlation coefficient between them is very high, 0.7045. Image variables including road surface, external appearance of buildings, green spaces and overall view of front garden showed 91.21~61.08% of total variance. Thus, the remains can be considered to be the error valiance or specific variance. In Fctor I, II and III, main components explaining the road surface image of front gardens are order, hardness, texture, color, gradient and rythm. As for the external appearance of b wilding, variables of color, hardness, stability, peculiality and shape revealed high values of factor load. For all variables, communality was drastically high and ellen values and common variance were found to be very high in Factor I. As for the front gardens, variables explaining volume and peculiarity were found to be the main components of Factor I. In Factor II and III, variables of factor load were tidiness, pleasantness.