• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1205-1214
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• 2007

We define a skew-symmetric double Rayleigh distribution by a symmetric double Rayleigh distribution, and derive an approximate maximum likelihood estimator(AML) and a moment estimator(MME) of a skewed parameter in a skew-symmetric double Rayleigh distribution, and hence compare simulated mean squared errors of those two estimators. We also compare simulated mean squared errors of two proposed estimators of reliability in two independent skew-symmetric double Rayleigh distributions.

• Journal of the Korean Data and Information Science Society
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• 제11권2호
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• pp.319-325
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• 2000

In this paper, we shall derive MLE's, modified MLE, MRE and UMVUE's of the shape and scale parameters in a generalized uniform distribution, and propose several estimators for the right-tail probability in a generalized uniform distribution using the proposed estimators for the shape and scale parameters. And we shall compare exactly MSE of the proposed estimators for the shape and the scale parameters, and compare numerically efficiencies for the several proposed estimators of the right-tail probability in a generalized uniform distribution by Monte Caslo methods.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.193-198
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• 1999

The estimation of parameters in regression models with multiplicative errors is usually based on the gamma or log-normal likelihoods. Under reciprocal misspecification, we compare the small sample efficiencies of two sets of estimators via a Monte Carlo study. We further consider the case where the errors are a random sample from a Weibull distribution. We compute the asymptotic relative efficiency of quasi-likelihood estimators on the original scale to least squares estimators on the log-transformed scale and perform a Monte Carlo study to compare the small sample performances of quasi-likelihood and least squares estimators.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.307-316
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• 2004

Principal Component Regression(PCR) and Partial Least Squares Regression(PLSR) are the two most popular regression techniques in chemometrics. In the field of chemometrics usually the number of regressor variables greatly exceeds the number of observation. So we have to reduce the number of regressors to avoid the identifiability problem. In this paper we compare PCR and PLSR techniques combined with various robust regression methods including regression depth estimation. We compare the efficiency, goodness-of-fit and robustness of each estimators under several contamination schemes.

• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.189-204
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• 2021

In a regression analysis, a single best model is usually selected among several candidate models. However, it is often useful to combine several candidate models to achieve better performance, especially, in the prediction viewpoint. Model combining methods such as stacking and Bayesian model averaging (BMA) have been suggested from the perspective of averaging candidate models. When the candidate models include a true model, it is expected that BMA generally gives better performance than stacking. On the other hand, when candidate models do not include the true model, it is known that stacking outperforms BMA. Since stacking and BMA approaches have different properties, it is difficult to determine which method is more appropriate under other situations. In particular, it is not easy to find research papers that compare stacking and BMA when regression model assumptions are violated. Therefore, in the paper, we compare the performance among model averaging methods as well as a single best model in the linear regression analysis when standard linear regression assumptions are violated. Simulations were conducted to compare model averaging methods with the linear regression when data include outliers and data do not include them. We also compared them when data include errors from a non-normal distribution. The model averaging methods were applied to the water pollution data, which have a strong multicollinearity among variables. Simulation studies showed that the stacking method tends to give better performance than BMA or standard linear regression analysis (including the stepwise selection method) in the sense of risks (see (3.1)) or prediction error (see (3.2)) when typical linear regression assumptions are violated.

• 한국의료질향상학회지
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• 제12권1호
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• pp.92-102
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• 2006

Background : Most hospitalized children will experience physical pain as well as psychological distress. Painful procedure can increase anxiety and fear of pediatric patients and their parents who do not have understanding logical of their disease and hospitalization. This study attempted to identify pain reduction in related to therapeutic intervention by age and environmental improvement. Methods : A total of 194 hospitalized children and their parents were investigated. Data collection period was 3 months from March to May 2004. Four instruments were used to collect the data : Faces Pain Rating Scale(FPRS), Heart rate, Oxygen saturation and Pain behavioral check list. The data were analyzed by a SPSS program and tested x2-test, t-test, ANCOVA. Results : 1. Age from 0 to 3, the Heart rate, FPRS, Oxygen saturation and Pain behavioral check list were significantly different in theraputic intervention group when compare to control group. 2. Age from 4 to 6, FPRS, Oxygen saturation and Pain behavioral check list were significantly different in theraputic intervention group when compare to control group. But the heart rate were not significantly different when compare to control group. 3. Age from 7 to 9, FPRS and Pain behavioral check list were significantly lower in therapeutic intervention group when compare to control group but Heart rate and Oxygen saturation were not significantly different when compare to control group. Conclusion : The results of this study concludes that most children experience acute pain during IV therapy and it can be reduced by age specific therapeutic intervention and by change of surrounding environment.

• Communications for Statistical Applications and Methods
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• 제25권4호
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• 가정과삶의질연구
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• 제13권4호
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• pp.139-150
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• 1995

This research is planned to compare a quantitative methodology and a qualitative methodology in the study of the household work. For these research tasks this study is centered on husbands' participation in the household work. First it is reviewed study precedent using a quantitative method and a qualitative method to compare a research methodology of the household work. It is selected a survey method of quantitative methodology and a depth interview of qualitative methodology, Second the data are collected through the questionnaire and the depth interview with three couples,. Third to compare a quantitative methodology and a qualitative methodology it is looked about problems in the concept the grouping the collection of data and the interpretation of household work.

• 품질경영학회지
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• 제49권2호
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• pp.145-159
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• 2021

Purpose: A statistical similarity evaluation to compare pharmacokinetics(PK) profile data between nonclinical and clinical experiments has become a significant issue on many drug development processes. This study proposes a new similarity index by considering important parameters, such as the area under the curve(AUC) and the time-series profile of various PK data. Methods: In this study, a new profile similarity index(PSI) by using the concept of a process capability index(Cp) is proposed in order to investigate the most similar animal PK profile compared to the target(i.e., Human PK profile). The proposed PSI can be calculated geometric and arithmetic means of all short term similarity indices at all time points on time-series both animal and human PK data. Designed simulation approaches are demonstrated for a verification purpose. Results: Two different simulation studies are conducted by considering three variances(i.e., small, medium, and large variances) as well as three different characteristic types(smaller the better, larger the better, nominal the best). By using the proposed PSI, the most similar animal PK profile compare to the target human PK profile can be obtained in the simulation studies. In addition, a case study represents differentiated results compare to existing simple statistical analysis methods(i.e., root mean squared error and quality loss). Conclusion: The proposed PSI can effectively estimate the level of similarity between animal, human PK profiles. By using these PSI results, we can reduce the number of animal experiments because we only focus on the significant animal representing a high PSI value.

• 대한핵의학회지
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• 제29권4호
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• pp.478-483
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• 1995

We compared the influences of reconstruction methods using $180^{\circ}$ or $360^{\circ}$ data upon contrasts and discriminating capability and diagnostic accuracy in $^{99m}Tc-MIBI$ stress/rest myocardial SPECT. We reviewed SPECT images reconstructed only with $180^{\circ}$ projection data or with $360^{\circ}$ data in 18 patients and in 11 normal subjects. To compare counts of surface structures and deep structures, we measured ape# posterior wall ratios in 11 normal subjects. To compare the contrasts of images, we measured apex/ventricle ratios. To compare contrasts between normal and diseased myocardial segments, we measured count ratios of defect and normal segments in 4 patients who had single coronary artery diseases. To compare diagnostic accuracy, we scored SPECT images made with $180^{\circ}$ and $360^{\circ}$ data segmentally. Sensitivity and specificity for the diagnosis of coronary artery disease and for the revelation of diseased arteries with both $180^{\circ}$ and $360^{\circ}$ SPECT images. If involved coronary arteries had more narrowing than 50% In coronary angiogram, we considered them as diseased arteries Apex/posterior wall ratios were not different significantly in normal subjects. Apex/ ventricle ratios in normal subjects were different significantly between $180^{\circ}$ and $360^{\circ}$ SPECT images. Defect/normal ratios were different significantly between $180^{\circ}$ and $360^{\circ}$ SPECT images in single vessel disease patients. The overall diagnostic accurracy was the same between $180^{\circ}$ and $360^{\circ}$ data collection. Sensitivity was 94% and specificity was 91% for both types of data collection in this sample population. Sensitivity and specificity of each coronary artery territory were not significantly different between the images made with $180^{\circ}$ and $360^{\circ}$ data. The images made with $180^{\circ}$ data had better contrast between ventricle and myocardium and between hypoperfused and normal myocardium, though no difference was found between the ratios of the myocardial counts of surface and deep structures. However, diagnostic sensitivities of diseased artery territories were not different significantly and so were overall diagnostic accuracy between both methods of making images with $180^{\circ}$ and $360^{\circ}$ data.