• Communications for Statistical Applications and Methods
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• 제14권3호
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• pp.593-600
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• 2007

Under repeated surveys, missing values often appear for various reasons and are replaced by new samples. It is investigated that the existing estimator in repeated survey by Jessen (1942), which has been originally developed for the new samples of fixed size, can be used in such situation where the size of new samples is random. It is shown that the proposed estimator has smaller variance than the sample mean.

• 한국임상수의학회지
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• 제28권4호
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• pp.422-426
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• 2011

For a national survey in which wide geographic region or an entire country is targeted, multi-stage sampling approach is widely used to overcome the problem of simple random sampling, to consider both herd- and animallevel factors associated with disease occurrence, and to adjust clustering effect of disease in the population in the calculation of sample size. The aim of this study was to establish sample size for estimating bovine tuberculosis (TB) in Korea using stratified two-stage sampling design. The sample size was determined by taking into account the possible clustering of TB-infected animals on individual herds to increase the reliability of survey results. In this study, the country was stratified into nine provinces (administrative unit) and herd, the primary sampling unit, was considered as a cluster. For all analyses, design effect of 2, between-cluster prevalence of 50% to yield maximum sample size, and mean herd size of 65 were assumed due to lack of information available. Using a two-stage sampling scheme, the number of cattle sampled per herd was 65 cattle, regardless of confidence level, prevalence, and mean herd size examined. Number of clusters to be sampled at a 95% level of confidence was estimated to be 296, 74, 33, 19, 12, and 9 for desired precision of 0.01, 0.02, 0.03, 0.04, 0.05, and 0.06, respectively. Therefore, the total sample size with a 95% confidence level was 172,872, 43,218, 19,224, 10,818, 6,930, and 4,806 for desired precision ranging from 0.01 to 0.06. The sample size was increased with desired precision and design effect. In a situation where the number of cattle sampled per herd is fixed ranging from 5 to 40 with a 5-head interval, total sample size with a 95% confidence level was estimated to be 6,480, 10,080, 13,770, 17,280, 20.925, 24,570, 28,350, and 31,680, respectively. The percent increase in total sample size resulting from the use of intra-cluster correlation coefficient of 0.3 was 22.2, 32.1, 36.3, 39.6, 41.9, 42.9, 42,2, and 44.3%, respectively in comparison to the use of coefficient of 0.2.

• International Journal of Contents
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• 제5권1호
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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.

• Communications for Statistical Applications and Methods
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• 제23권2호
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Journal of the Korean Statistical Society
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• 제20권1호
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• pp.67-76
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• 1991

The empirical Bayes version involves ″independent″ repetitions(a sequence) of the component decision problem. With the varying sample size possible, these are not identical components. However, we impose the usual assumption that the parameters sequence $\theta$=($\theta$$_1$, $\theta$$_2$, …) consists of independent G-distributed parameters where G is unknown. We assume that G $\in$ g, a known family of distributions. The sample size $N_i$ and the decisin rule $d_i$ for component i of the sequence are determined in an evolutionary way. The sample size $N_1$ and the decision rule $d_1$$\in$ $D_{N1}$ used in the first component are fixed and chosen in advance. The sample size $N_2$and the decision rule $d_2$ are functions of *see full text($\underline{X}^1$equation omitted), the observations in the first component. In general, $N_i$ is an integer-valued function of *see full text(equation omitted) and, given $N_i$, $d_i$ is a $D_{Ni}$/-valued function of *see full text(equation omitted). The action chosen in the i-th component is *(equation omitted) which hides the display of dependence on *(equation omitted). We construct an empirical Bayes decision rule for estimating normal mean and show that it is asymptotically optimal.

• 동아시아경상학회지
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• 제7권4호
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• pp.41-49
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• 2019

Purpose - This paper empirically investigates what factors contribute to corporate investments under financial constraint condition in the Korean stock market. In the paper, tangible assets' growth rate and fixed assets' growth rate were employed as investment performance and total assets were also used for comparison purpose. Research design and methodology - Samples are constructed by manufacturing firms listed on the stock market of Korea as well as those who settle accounts in December from 2001 to 2018. Financial institutions are excluded from the sample as their accounting procedures, governance and regulations differ. This study adopted a fixed panel regression model to assess the sample construction including yearly and cross-sectional data. Results - This results support the literatures that major shareholders showed positive significance to investment in financially unconstrained firms and no significance to investment in financially constrained firms. ROA showed positive significance to investment in financially unconstrained and constrained firms, whereas firm size showed negative significance to investment in financially unconstrained and constrained firms. Debt showed no positive significance to investment in financially unconstrained firms and negative significance to investment in financially constrained firms. Conclusions - This paper documented evidence that ROA and firm size are important factors to investment irrespective of firms' financial constraints. And this paper also supports that major shareholders give positive impact to investments in financially unconstrained firms. This means that financial constraints itself rule corporate' investment decision in financially constrained firms.

• Journal of the Korean Data and Information Science Society
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• 제20권5호
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• pp.887-894
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• 2009

The two-stage minimum risk point estimation of mean, the probability of success in a sequence of Bernoulli trials, is considered for the case where loss is taken to be symmetrized relative squared error of estimation, plus a fixed cost per observation. First order asymptotic expansions are obtained for large sample properties of two-stage procedure. Monte Carlo simulation is carried out to obtain the expected sample size that minimizes the risk and to examine its finite sample behavior.

• Computers and Concrete
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• 제7권5호
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• pp.469-482
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• 2010

This paper investigates the concrete permeability through a numerical and statistical approach. Concrete is considered as a random heterogeneous composite of three phases: aggregates, interfacial transition zones (ITZ) and matrix. The paper begins with some classical bound and estimate theories applied to concrete permeability and the influence of ITZ on these bound and estimate values is discussed. Numerical samples for permeability analysis are established through random aggregate structure (RAS) scheme, each numerical sample containing randomly distributed aggregates coated with ITZ and dispersed in a homogeneous matrix. The volumetric fraction of aggregates is fixed and the size distribution of aggregates observes Fuller's curve. Then finite element method is used to solve the steady permeation problem on 2D numerical samples and the overall permeability is deduced from flux-pressure relation. The impact of ITZ on overall permeability is analyzed in terms of ITZ width and contrast ratio between ITZ and matrix permeabilities. Hereafter, 3680 samples are generated for 23 sample sizes and 4 contrast ratios, and statistical analysis is performed on the permeability dispersion in terms of sample size and ITZ characteristics. By sample theory, the size of representative volume element (RVE) for permeability is then quantified considering sample realization number and expected error. Concluding remarks are provided for the impact of ITZ on concrete permeability and its statistical characteristics.

• 대한산업공학회지
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• 제25권4호
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• pp.448-458
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• 1999

This paper proposes sequential control charts with an upper bound on sample size. Existing sequential control charts have no restriction on the number of observations at a sampling point. For situations where sampling and testing an item is time-consuming or expensive, sequential control charts may not be directly applied. When the number of observations in a sampling point reaches the upper bound and there is no out-of-control signal, the proposed cumulative sequential control chart defers the decision to the next sampling point of which starting value is the value of the current statistic. Two Markov chains, inner and outer chains, are used to derive the formulas for evaluating the performance of the proposed chart. It is compared with $\bar{X}$ and cumulative sum control charts with fixed and variable sample sizes. The fast initial response (FIR) feature is studied. Guidelines for the design of the proposed charts are also given.

• 대한의생명과학회지
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• 제13권4호
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• pp.361-368
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• 2007

Biological samples can be fixed either by chemical method by using chemical solution or physical methods by using heat treatment. The problem in traditional heat fixation is unsatisfactory quality due to uneven heat conduction in specimen and loss of inner cell contents. Chemical fixation method also bears several intrinsic problems like the limit in specimen size, time consumption in fixative impregnation, and loss of low molecular weight cell components. These factors deteriorate the quality of fixed specimen, thus limit the magnification and contrast of tissue pictures. Microwave heat has been reported to be a good alternative to current chemical methods to overcome these problem. In this study, we tried to introduce the microwave energy method to routine fixation work in hospital. We replaced chemical fixative with saline to provide moderate reaction condition, and used frozen section to reduce time for sample preparation. Temperature was measured at each experiment. The fixation of rat kidney tissue with 2.45 GHz electromagnetic wave and saline showed similar result to the control group fixed with traditional chemical method. Human tumor tissue fixed with 2.45 GHz electromagnetic in frozen section was improved in terms of histochemistry of PAS and immunohistochemistry of tumor marker like cytokeratin. Total turnaround time was reduced from $24\sim38$ h to to $2\sim4$ h. In conclusion, the quality of samples prepared by microwave heating method was at least as good as that of traditional method. If the condition for the fixation of different specimens is standardized, this new method could be applied to routine work in hospital, and could save working time as well.