• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.733-742
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• 1998

For industrial and medical lifetime data, the generalized log-gamma regression model is considered. Then the Bayesian analysis for the generalized log-gamma regression with censored data are explained and following the data augmentation (Tanner and Wang; 1987), the censored data is replaced by simulated data. To overcome the complicated Bayesian computation, Makov Chain Monte Carlo (MCMC) method is employed. Then some modified algorithms are proposed to implement MCMC. Finally, one example is presented.

• Journal of the Korean Data and Information Science Society
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• v.5 no.1
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• pp.59-66
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• 1994

Heller and Simonoff(1990) compared several methods of estimating the regression coefficient in a modified proportional hazards model, when the response variable is subject to censoring. We give another method of estimating the parameters in the model which also allows the dependent variable to be censored and the error distribution to be unspecified. The proposed method differs from that of Miller(1976) and that of Buckely and James(1979). We also obtain the variance estimator of the coefficient estimator and compare that with the Buckely-James Variance estimator studied by Hillis(1993).

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.57-66
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• 2001

This study was performed to determine adsorption equilibrium moisture contents of rough rice, brown rice, white rice and rice hull grown in Korea. EMC values were measured by static method using saturated salt solutions at three temperature levels of 20$\^{C}$, 30$\^{C}$ and 40$\^{C}$, and eight relative humidity levels in the range from 11.2% to 85.0%. The measured EMC values were fitted to modified Henderson, Chung-Pfost, and modified Oswin models by using nonlinear regression analysis. The results of comparing root mean square errors for three models showed that modified Henderson and Chung-Pfost models could serve as good models, and that modified Oswin model could not be applicable to rough rice, brown rice, white rice and rice hull.

• Health Policy and Management
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• v.4 no.2
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical variables.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.875-885
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• 2012

In this study, the total precipitation amount in Jeju Island was estimated with the simulated precipitation for ungauged stations missing precipitation data using the spatial precipitation analysis. The missing data were generated through the modified multiple linear regression in this study, and the analysis of spatial precipitation was conducted with the PRISM(Parameter-elevation Regression on Independent Slope Model). The generated data with modified multiple linear regression model have similar pattern with original data. Thus, the model in this study shows good applicability to estimate the missing data. The difference of annual average precipitation between Case 1 (original data) and Case 2 (modified data) appears very small ratio which is about 1.5%. However, the difference of annual average precipitation according to elevation shows the large ratio up to 37.4%. As the results, the method of estimating missing data in this study would be useful to calculate the total precipitation amount at the low station density area and the places with the high spatial variation of precipitation.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.155-158
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• 1999

This paper discusses the validity of models to predict the compressive strength of concrete subjected to various temperature histories and the shortcomings of existing rate constant model and apparent activation energy concept. Based on the discussion, a modified rate constant model is proposed. The modified rate constant model, in which apparent activation energy is a nonlinear function of curing temperature and age, accurately estimates the development of the experimental compressive strengths by a few researches. Also, the apparent activation energy of concrete cured with high temperature decreases rapidly with age, but that cured with low temperature decreases gradually with age. Finally a generalized model to predict apparent activation energy and compressive strength is proposed, which is based on the regression results.

• International Commerce and Information Review
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• v.16 no.5
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• pp.409-433
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• 2014

In this paper, I estimate long-run elasticities of US real GDP and real exchange rate between Korean Won and US Dollar on export of Korean goods to US and analyze changes in their trend by using VECM and rolling regression with a fixed window. For the purposes I use the year data from 1990 to 2013 which are selected from UNCTAD, Korea Trade Association(KTA), and Bank of Korea(BOK). The results are that the long-run elasticities of US real GDP vary from 2.849 to 2.938 for the period from 1990 to 2013 depending on the models in VECM and all of them are significant statistically. The elasticities of real exchange rate between Korean WON and US Dollar vary from 0.962 to 0.967 for the same period depending on the models in VECM and all of them are significant statistically. In case of the results through the OLS and the rolling regression, the long-run elasticities of US. real GDP are 3.015 for Basic Model, 2.949 for the modified Model 1, and 2.125 for the modified Model 2 for the period from 1990 to 2013 depending on the models and all of them are significant statistically. The average of long-run elasticities of real US GDP before the global financial crisis of 2008 is greater than that after the global financial crisis of 2008. On the other hand, the long-run elasticities of real exchange rate between Korean WON and US $ are 0.347 for Basic Model, 0.566 for the modified Model 1, and -0.217 for the modified Model 2 for the same period and all of them are significant statistically except for the modified Model 2. The average of long-run elasticities of real exchange rate before the global financial crisis of 2008 is greater than that after the global financial crisis of 2008.

• Advances in environmental research
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• v.3 no.3
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• pp.231-251
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• 2014

The present study examines the phosphate adsorption potential and behavior of mixture of Ground Burnt Patties (GBP), a solid waste generated from cooking fuel used in earthen stoves and Red Soil (RS), a natural substance in fixed bed column mode operation. The characterization of adsorbent was done by Proton Induced X-ray Emission (PIXE), and Proton Induced ${\gamma}$-ray Emission (PIGE) methods. The FTIR spectroscopy of spent adsorbent reveals the presence of absorbance peak at $1127cm^{-1}$ which appears due to P = O stretching, thus confirming phosphate adsorption. The effects of bed height (10, 15 and 20 cm), flow rate (2.5, 5 and 7.5 mL/min) and initial phosphate concentration (5 and 15 mg/L) on breakthrough curves were explored. Both the breakthrough and exhaustion time increased with increase in bed depth, decrease in flow rate and influent concentration. Thomas model, Yoon-Nelson model and Modified Dose Response model were used to fit the column adsorption data using nonlinear regression analysis while Bed Depth Service Time model followed linear regression analysis under different experimental condition to evaluate model parameters that are useful in scale up of the process. The values of correlation coefficient ($R^2$) and the Sum of Square Error (SSE) revealed the Modified Dose Response model as the best fitted model to the experimental data. The adsorbent mixture responded effectively to the desorption and reusability experiment. The results of this finding advocated that mixture of GBP and RS can be used as a low cost, highly efficient adsorbent for phosphate removal from aqueous solution.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.241-247
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• 2021

This study analyzed the changes in explanatory power of the modified Jones model(1995) for estimating the amount of accruals for Korean Stock Market listed companies from 1990 to 2019. We hypothesized that if the properties of financial variables used in the existing model change over time or change in discretionary ratios, the model's explanatory power will change. As the result of regression models, I found that the explanatory power of the modified Jones model(1995) gradually declined over time. The results may be derived from the increase in accruals itself and the changes in the distribution of variables contained in the model. The results of this research's chronological approach are expected to give important implications to both academic researchers and accounting information users.