• Communications for Statistical Applications and Methods
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• 제13권1호
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• pp.141-150
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• 2006

Penalized likelihood regression for exponential families have been considered by Kim (2005) through smoothing parameter selection and asymptotically efficient low dimensional approximations. We derive approximate Bayesian confidence intervals based on Bayes model associated with lower dimensional approximations to provide interval estimates in penalized likelihood regression and conduct empirical studies to access their properties.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.29-33
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• 2001

We propose fuzzy least-squares regression analysis by few error term data and test the slop by fuzzy hypotheses membership function for fuzzy number data with agreement index. Finding the agreement index by area for fuzzy hypotheses membership function and membership function of confidence interval, we obtain the results to acceptance or reject for the test of fuzzy hypotheses.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1247-1253
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• 2008

In this paper, we propose a interval censored regression spline model with a variance function (non-constant variance that depends on a predictor). Simulation studies show our estimates from MCECM algorithm are consistent, but biased when the sample size is small because of boundary effects. Also, we examined how the distribution of $x_i$ affects the converging speed of these consistent estimates.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.277-289
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• 2003

We propose modified exact inferential methods in logistic regression model. Exact conditional distribution in logistic regression model is often highly discrete, and ordinary exact inference in logistic regression is conservative, because of the discreteness of the distribution. For the exact inference in logistic regression model we utilize the modified P-value. The modified P-value can not exceed the ordinary P-value, so the test of size $\alpha$ based on the modified P-value is less conservative. The modified exact confidence interval maintains at least a fixed confidence level but tends to be much narrower. The approach inverts results of a test with a modified P-value utilizing the test statistic and table probabilities in logistic regression model.

• 응용통계연구
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• 제26권5호
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• pp.737-746
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• 2013

Tobin (1958)에 의해 처음 소개된 절단 회귀모형에서 베이지안 추정은 최대가능도 추정보다 실제값에 가까운 것으로 알려져 있으나 베이지안 방법론이 구간추정 문제에 있어서도 성공적으로 작동할 수 있을 지에 대해서는 알려진 바가 없다. 일반적으로 베이지안 방법론에서 사전분포는 분석자의 사전정보를 반영하기 때문에 주관적인 분석이 될 수 밖에 없는데, 이렇게 주관적인 분석에서는 빈도학파들이 요구하는 기준을 따르기 어렵다. 그러나 무정보사전분포는 때때로 빈도학파적 특성을 갖는 베이지안 추론을 가능하게 한다. 본 연구에서는 절단 회귀모형에서 무정보사전분포에 의한 베이지안 신뢰구간의 빈도학파적 특성을 살펴보고 최대가능도 추정 신뢰구간과 포함확률을 비교한다. 이를 통해 최대가능도 추정의 표준오차가 과소 추정되고 있음 밝힌다.

• The Korean Journal of Physiology
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• 제8권2호
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• pp.33-44
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• 1974

The electrocardiogram of frogs were obtained in winter (January), spring (April), summer (July) and autumn (September and November). Electrocardiograms were recorded applying electrodes to the atria, ventricle and apex of the heart by unipolar or bipolar leads. V wave was recorded prior to P wave, for the presence of the sinus venosus which controls the automaticity of the frog heart, in four seasons. Regardless of the leads or the position of the electrodes P wave was diphasic and wide. According to the rise of temperature the rate of heart beat was increased, and V-P and P-R interval were shortened. Two regression line between R-R interval and both V-P interval and P-R interval were drawn. These were calculated as V-P interval=1 0.276R-R $interva1+0.067{\pm}0.15$ (sec.) and P-R interval=0.179R-R $interva1+0.155{\pm}0.1$ (sec). From these calculation the larger gradient of V-P interval than P-R interval was suggestive that the heart rate is more dependent on the changes of V-P interval than that of P-R interval. Changes of the heart rate were also measured in four seasons and artificial temperatures. Two regression lines between the heart rate (H.H.) and both seasonal temperature (T) and artificial temperature, were drawn. These two lines were calculated as H.R.=20+3.71 (T-10) and H.R.=32+1.425 T respectively. From two gradients of the above equations it is considered that the changes of the heart rate in artificial temperature were milder than that in seasonal temperature. The number of RBC and WBC of frogs were measured in four seasons and a tendency of the changes was observed according to the seasonal variation.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.361-370
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• 2003

Those who are interested in making inferences concerning linear combination of valiance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods. The methods are applied to a numerical example and recommendations are given for choosing a proper interval.

• 한국기계가공학회지
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• 제12권4호
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• pp.87-92
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• 2013

In this study, we carried out the turning of plastic mold steel(STAVAX) with whisker reinforced ceramic tool(WA1) and analyzed ANOVA(Analysis of Variance) test. Multi-regression analysis was performed to find influential factors to surface roughness and to derive regression equation. Results are follows: From ANOVA test and confidence interval analysis of surface roughness, We found that influential factors to surface roughness was feed rate, cutting speed and depth of cut in order. From multi-regression analysis, we derived regression equation of STAVAX. it's coefficient of determination($R^2$) was 0.945 and It means that regression equation is significant. From experimental verification, we confirmed that surface roughness was predictable by regression equation. Compared with former research, we confirmed that increase of feed rate is the main cause of the growing of surface roughness and cutting force.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.551-562
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• 1995

We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.591-601
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• 2005

The results of fuzzy linear regression are very sensitive to irregular data. When this points exist in a set of data, a fuzzy linear regression model can be incorrectly interpreted. The purpose of this paper is to detect irregular data and to propose robust fuzzy linear regression based on M-estimators with triangular fuzzy regression coefficients for crisp input-output data. Numerical example shows that irregular data can be detected by using the residuals based on M-estimators, and the proposed robust fuzzy linear regression is very resistant to this points.