• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.457-464
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• 2012

Small area estimation is a statistical inference method to overcome the large variance due to the small sample size allocated in a small area. Recently some nonparametric estimators have been applied to small area estimation. In this study, we suggest a nonparametric mixed effect small area estimator using kernel smoothing and compare the small area estimators using labor statistics.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.1
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• pp.10-17
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• 1999

The present work presents condensation heat transfer and pressure drop data for the flow of R-12 in flat extruded aluminum tubes with small hydraulic diameters. The tube outside dimensions are $18mm(width){\times}1.7mm(height)$. Three types of internal geometry with the same outside dimensions are tested : sample 1 (7 tube holes), sample 2 (13 tube holes) and sample 3 (7 tube holes, micro-fin). The overall heat transfer coefficient is obtained for air-to-refrigerant heat transfer, and the Wilson plot method is used to determine the heat transfer coefficient for refrigerant flow. The sample 2 and sample 3 show significantly higher performance than sample 1. The heat transfer rates for the sample 2 and sample 3 are 9% and 12% higher, respectively, than sample 1. The friction factors for the sample 2 and sample 3 are 11.9% and 2.4% higher, respectively, than sample 1.

• Journal of the Korean Wood Science and Technology
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• v.18 no.3
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• pp.53-68
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• 1990

This research has been executed for maximization of lumber yield and more efficient use of small diameter logs. Sample logs from thinnings carne from densed artificial stands at the Kwangnung Experimental Forests situated in the central region of Korean peninsula. Species of sample logs were obtained to execute sawing and strength test for larch, and lumber strength test in full size for pitch pine and Korean pine. A survey on sawmills consuming domestic logs was carried out to know sawmill production, costs and utilization structure of lumber as a guide to business analysis. Results showed that sawing pattern from small logs less than 15cm in diameter was necessary to cut 9cm by 9cm square per one log in order to obtain high lumber recovery and provide for wide market needs. The total lumber yield of squares plus side boards was 56 percent to 58 percent from small logs and the yield for log sweep in 30 percent decreased by 24.5 percent in sawing production, compared to yield for straight logs. In sawing efficiency, production of lumber by twin band saw could be improved 238 percent higher than lumber of the same species produced by conventional sawmilling methods, and sawing accuracy with twin band saw was much higher at the lumber production than band saw. Lumber from the small larch logs has shown 70 knots per $m^2$ on its faces and also lumber showed lots of face checkings by air drying on the yard, compared to other species. MOR in bending of lumber in full size from small logs of larch was found ranging from 380kg/$cm^2$ to 460kg/$cm^2$, resulting in 40 percent less than the strength from clear small specimens. In lumber containing knots, cross grain, etc, longitudinal stress wave speed was delayed about 48 percent by defects in lumber from both larch and pitch pine logs. The surveyed sample sawmills consumed the domestic logs at the rate of 54 percent to 84 percent in the total timber consumption, showing high consumption at mills located in the mountains.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.1097-1102
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• 2009

Classification of subjects with unknown distribution in small sample size setup may involve order-restricted constraints in multivariate parameter setups. Those problems makes optimality of conventional likelihood ratio based statistical inferences not feasible. Fortunately, Roy (1953) introduced union-intersection principle(UIP) which provides an alternative avenue. Redescending M-estimator along with that principle yields a considerably appropriate robust testing procedure. Furthermore, conditionally distribution-free test based upon exact permutation theory is used to generate p-values, even in small sample. Applications of this method are illustrated in simulated data and read data example (Lobenhofer et al., 2002)

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.9-20
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• 1990

The purpose of this paper is to propose the modified semiparametric estimators for survival function in the Cox's regression model with randomly censored data based on Tsiatis and Breslow estimators, and present their asymptotic variances estimates. The proposed estimators are compared to Tsiatis, Breslow, and Kaplan-Meier estimators through a small-sample Monte Carlo study. The simulation results show that the proposed estimators are preferred for small sample sizes.

• Journal of the Korean Statistical Society
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• v.9 no.2
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• pp.181-193
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• 1980

A class of nonparametric estimators of the ratio of scale parameters is proposed. The estimators are based on the distribution-free rank-like test suggested by Fligner and Killeen (1976). An explicit form of the estimator is the median of the ratios of absolute deviations from the combined sample median. A small-sample Monte Carlo study shows that the proposed estimator is more efficient than the Bhattacharyya (1977) estimator. The proposed estimator is is reasonably insensitive to small failures in the assumption of equal medians. A modified estimator is also considered when the meidans are unequal.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.135-149
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• 1994

We discussed a comparison of distribution-free two-sample procedures based on placements or ranks. Iterative asymptotic distribution of both two-sample procedures is studies and small sample Monte Carlo simulation results are presented. Also, we proposed the Hodges-Lehmann type location estimator based on linear placement statistics.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.595-610
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• 2013

Testing of order-restricted alternative hypothesis in $2{\times}k$ contingency tables can be applied to various fields of medicine, sociology, and business administration. Most testing methods have been developed based on a large sample theory. In the case of a small sample size or unbalanced sample size, the Type I error rate of the testing method (based on a large sample theory) is very different from the target point of 5%. In this paper, the exact testing method is introduced in regards to the testing of an order-restricted alternative hypothesis in categorical data (particularly if a small sample size or extreme unbalanced data). Power and exact p-value are calculated, respectively.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.421-430
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• 2006

In sample survey sample designs are performed by geographically-based domain such as countries, states and metropolitan areas. However mostly statistics of interests are smaller domain than sample designed domain. Then sample sizes are typically small or even zero within the domain of interest. Shin and Lee(2003) mentioned Spatial Autoregressive(SAR) model in small area estimation model-based method and show the effectiveness by MSE. In this study, Bayesian Auto-Poisson Model is applied in model-based small area estimation method and compare the results with SAR model using MSE ME and bias check diagnosis using regression line. In this paper Survey of Disability, Aging and Cares(SDAC) data are used for simulation studies.