• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.89-97
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• 1994

We consider the linear calibration model: $y_1={\alpha}+{\beta}x_i+{\sigma}{\varepsilon}_i$, i = 1, ${\cdots}$, n, $y={\alpha}+{\beta}x+{\sigma}{\varepsilon}$ where ($y_1$, ${\cdots}$, $y_n$, y) stands for an observation vector, {$x_i$} fixed design vector, (${\alpha}$, ${\beta}$) vector of regression parameters, x unknown true value of interest and {${\varepsilon}_i$}, ${\varepsilon}$ are mutually uncorrelated measurement errors with zero mean and unit variance but otherwise unknown distributions. On the basis of simple small-sample low-noise approximation, we introduce a new method of comparing the mean squared errors of the various competing estimators of the true value x for finite sample size n. Then we show that a class of estimators including the classical and the inverse estimators are consistent and first-order efficient within the class of all regular consistent estimators irrespective of type of measurement errors.

• Korean Journal of Veterinary Service
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• v.25 no.1
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• pp.31-37
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• 2002

Major hazards existed in slaughterhouse are pathogenic microorganisms originated from intestinal microflora of slaughtered animals. This study was intended for the identification of microbial contamination sources during pork slaughtering in small plants. Total aerobic bacteria, Coliform group, Salmonella spp, Listeria monocytogenes, and Campylobacter jejuni/coli were isolated from the surface sample of pork carcasses. Contamination level among different sampling points of ham, belly and neck did not showed statistical differences. Therefore, the mixed sampling from belly and neck of carcass could be effective for microbiological monitoring. Isolation rates of pathogenic microorganisms showed Salmonella spp 20.9%, Listeria monocytogenes 10.5%, and Campylobacter jejuni/coli 8.1% from 296 sampling points. High prevalence rate of Salmonella spp indicated that the contamination of intestinal microflora occurred due to unsanitary processing control, which required HACCP system in small plants. It was recommended that the prerequisite program should be a key factor for a successful HACCP system implementation especially in small size slaughterhouse.

• Journal of Fashion Business
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• v.19 no.6
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• pp.14-27
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• 2015

This study explores the comparison of body image, body satisfaction, and clothing behaviors between Korean and British young women. Body image was measured by two methods: visual and verbal. For the data analysis, the Statistical Package for Social Science (SPSS) Version 16.0 for Windows was used to provide descriptive statistics, an independent sample t-test, and paired sample t- tests were applied in this study. Our results show that Korean and British female college students perceived ideal-body images that were smaller than their self defined body images. The ideal and self-images were significantly different in both groups. Both groups were dissatisfied with their own body size. The study was limited to a small sample size. Future studies using more participants from a more diverse age group and ethnic groups are recommended. The study will help marketers and retailers develop new products and new markets aimed at Korean and British women related to body image and body satisfaction.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.133-139
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• 2017

In this paper, we describe a permutation procedure in which we compute a resampling probability value and empirical quantile limits for Split-Half measure of internal reliability. We use the Split-Half reliability coefficient given by two simple methods, the Spearman-Brown formula and the two-part coefficient alpha. The use of a permutation test for Split-Half reliability coefficient is highlighted as a valuable tool when the sample sizes are small and necessary assumptions cannot be met. The permutation tests for Split-Half reliability coefficient are illustrated with an example analysis of two survey data with a sample size of 15 and 35, respectively, and a hypothetical data with a sample size of 5.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.53-64
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• 2022

High dimensional time series is gaining considerable attention in recent years. The sparse vector heterogeneous autoregressive (VHAR) model proposed by Baek and Park (2020) uses adaptive lasso and debiasing procedure in estimation, and showed superb forecasting performance in realized volatilities. This paper extends the sparse VHAR model by considering non-convex penalties such as SCAD and MCP for possible bias reduction from their penalty design. Finite sample performances of three estimation methods are compared through Monte Carlo simulation. Our study shows first that taking into cross-sectional correlations reduces bias. Second, nonconvex penalties performs better when the sample size is small. On the other hand, the adaptive lasso with debiasing performs well as sample size increases. Also, empirical analysis based on 20 multinational realized volatilities is provided.

• Fashion & Textile Research Journal
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• v.3 no.1
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• pp.61-69
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• 2001

The purpose of this study was to analyze the purchasing behavior related factors of Small Store User in Yhasi street of Dong-Sung Ro, Daegu. Frequency, $X^2$-test MANOVA, ANOVA and Duncan multiple range test were used to analyze the sample. The results of this study were as follows: 1) The largest sample were as follows: un married female, college students of twenties, 101-200 thousand won for salaries. 2) The factors of purchasing behavior were classified into 8 factors, enjoy shopping, store image, unique goods, culture space, salesperson, low price, information seeking, value via price orientation. 3) There were significant differences found between attitude on information source, number of seeking store, music in shop, music sound, size, display, price, street, in their factors of purchasing behavior (unique goods, value via price, low price, store image, enjoy shopping) 4) There were significant differences found between demographic characteristics (personal sales, location, transportation) in their factors of purchasing behavior (salesperson, cultural space, store image).

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.1
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• pp.41-60
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• 1998

This paper derives a consistent and bias corrected extension of Akaike's Information Criterion (AIC), $AIC_{bc}$, based on Kullback-Leibler information. This criterion has terms that penalize the overparametrization more strongly for small and large samples than that of AIC. The overfitting problem of the asymptotically efficient model selection criteria for small and large samples will be overcome. The $AIC_{bc}$ also provides a consistent model order selection. Thus, it is widely applicable to data with small and/or large sample sizes, and to cases where the number of free parameters is a relatively large fraction of the sample size. Relationships with other model selection criteria such as $AIC_c$ of Hurvich, CAICF of Bozdogan and etc. are discussed. Empirical performances of the $AIC_{bc}$ are studied and discussed in better model order choices of a linear regression model using a Monte Carlo experiment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.151-157
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• 2019

This study is about the process capability index (PCI). In this study, we introduce several indices including the index $C_{PR}$ and present the characteristics of the $C_{PR}$ as well as its validity. The difference between the other indices and the $C_{PR}$ is the way we use to estimate the standard deviation. Calculating the index, most indices use sample standard deviation while the index $C_{PR}$ uses range R. The sample standard deviation is generally a better estimator than the range R. But in the case of the panel process, the $C_{PR}$ has more consistency than the other indices at the point of non-conforming ratio which is an important term in quality control. The reason why the $C_{PR}$ using the range has better consistency is explained by introducing the concept of 'flatness ratio'. At least one million cells are present in one panel, so we can't inspect all of them. In estimating the PCI, it is necessary to consider the inspection cost together with the consistency. Even though we want smaller sample size at the point of inspection cost, the small sample size makes the PCI unreliable. There is 'trade off' between the inspection cost and the accuracy of the PCI. Therefore, we should obtain as large a sample size as possible under the allowed inspection cost. In order for $C_{PR}$ to be used throughout the industry, it is necessary to analyze the characteristics of the $C_{PR}$. Because the $C_{PR}$ is a kind of index including subgroup concept, the analysis should be done at the point of sample size of the subgroup. We present numerical analysis results of $C_{PR}$ by the data from the random number generating method. In this study, we also show the difference between the $C_{PR}$ using the range and the $C_P$ which is a representative index using the sample standard deviation. Regression analysis was used for the numerical analysis of the sample data. In addition, residual analysis and equal variance analysis was also conducted.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.27-38
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• 1995

In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.

• International Journal of Contents
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• v.5 no.1
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• pp.37-45
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• 2009

This paper empirically tests pecking order theory. Korean listed firms are used as the samples. On the whole we find supportive results for pecking order theory. The fixed effect model on the whole period shows that as pecking order theory suggests that debt ratio decreases as cash flow. ROA, physical assets, and firm size increase. Again, it is shown that corporate debt ratio significantly decreases as cash flow or ROA increases in every sub-sample, which coincides with the prediction of pecking order theory. Corporate debt ratio significantly decreases as physical assets or jinn size increases in case of the whole sample, pre-financial crisis period, and the sub-samples by q-ratio, which also supports the prediction of pecking order theory. Statistical significance of the coefficients of physical assets or firm size completely disappears after Korean financial crisis. Perhaps it is because the role of physical assets or firm size as a mitigator of information asymmetry significantly weakens after the financial crisis as Korean financial market becomes more transparent. For small firms only size variable is negatively and significantly related with debt to assets. It seems that size is an important factor for smaller firms in making financing decision.