• Journal of the Korean Data and Information Science Society
• /
• v.24 no.3
• /
• pp.533-541
• /
• 2013

In this study, a simple principal component analysis using Lasso is proposed. This method consists of two steps. The first step is to compute principal components by the principal component analysis. The second step is to regress each principal component on the original data matrix by Lasso regression method. Each of new principal components is computed as the linear combination of original data matrix using the scaled estimated Lasso regression coefficient as the coefficients of the combination. This method leads to easily interpretable principal components with more 0 coefficients by the properties of Lasso regression models. This is because the estimator of the regression of each principal component on the original data matrix is the corresponding eigenvector. This method is applied to real and simulated data sets with the help of an R package for Lasso regression and its usefulness is demonstrated.

• Communications for Statistical Applications and Methods
• /
• v.25 no.5
• /
• pp.489-499
• /
• 2018

Jeonse is a unique property rental system in Korea in which a tenant pays a part of the price of a leased property as a fixed amount security deposit and gets back the entire deposit when the tenant moves out at the end of the tenancy. Jeonse deposit is very important in the Korean real estate market since it is directly related to the residential property sales price and it is a key indicator to predict future real estate market trend. Jeonse deposit data shows a skewed and heteroscedastic distribution and the commonly used mean regression model may be inappropriate for the analysis of Jeonse deposit data. In this paper, we apply a Bayesian quantile regression model to analyze Jeonse deposit data, which is non-parametric and does not require any distributional assumptions. Analysis results show that the quantile regression coefficients of most explanatory variables change dramatically for different quantiles. The regression coefficients of some variables have different signs for different quantiles, implying that even the same variable may affect the Jeonse deposit in the opposite direction depending on the amount of deposit.

• Journal of Korea Water Resources Association
• /
• v.31 no.1
• /
• pp.59-69
• /
• 1998

A regression model with basin physiographic characteristics as independent variables was calibrated for regional flood frequency analysis. In case that high correlations existing among the independent variables the ridge regression has been known to have capability of overcoming the problems of multicollinearity. To optimize the ridge regression model the cost function including regularization parameter must be minimized. In this research the genetic algorithm was applied on this optimization problem. The genetic algorithm is a stochastic search method that mimic the metaphor of natural biological heredity. Using this method the regression model could have optimized and stable weights of variables.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.05e
• /
• pp.49-52
• /
• 2003

The performance of insulators under contaminated conditions is the underlying and the most factor that determines insulation design for outdoor applications, Among the contamination factors, The sea salt is the most dangerous factor, and the salt factor have closed relation with climatic conditions, such as wind, temperature, humidity and so on, Effect of these factors to insulation system is different of each other, and need to show the correlation by multiple regression analysis techniques. In this paper, predicted and analyzed equivalent salt deposit density (ESDD) by change climatic condition through multiple regression analysis.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.11 no.3
• /
• pp.41-47
• /
• 2012

Surface roughness is widely used as an index for processing degree of accuracy. Recently, regression analysis to predict the machining results are actively used to characterize a cutting operations. In the past, diamond machining had been used for ultra precision cutting operation, but now industrial diamond tools like PCD(Polycrystaline Diamond) has been widely used in ultraprecision machining of nonferrous metals. In this study, the authors focus on the effect of PCD tool property on the surface roughness of different types of aluminum alloy after cutting process by CNC operated lathe. Based on the regression analysis approach on a surface roughness data obtained by experiment, predictive analysis of surface roughness is effective to achieve better surface quality.

• Food Science and Biotechnology
• /
• v.14 no.2
• /
• pp.249-254
• /
• 2005

The relationship between Sigumjang gas chromatographic patterns precisely analyzed with capillary column and ranked order in sensory analysis was investigated by stepwise multiple regression analysis. Highly predictable multiple regression models were obtained in the analysis. Ninety percent of the Sigumjang aroma was explained by the regression models at step 15 in four transformation except for absolute value transformed with root square and relative value transformed with logarithm. The aroma of Sigumjang was most affected by 2,3-dimethylpyrazine at absolute value and absolute value transformed with logarithm and by 2-furancarboxaldehyde in other transformation. The quality of sigumjang was highly affected by ${\beta}$-phallendrenal, methylpyrazine, tetramethylpyrazine, 5-methyl-2-furancarboxaldehyde, unknown 2, octanoic acid, 4-ethylphenol, methyl 10,13-octadecanoate and ethyl linoleate.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.37 no.1
• /
• pp.29-43
• /
• 2012

We design a DEA-AR model using multiple regression analysis with new methods which limit weights. When there are multiple input and single output variables, our model can be used, and the weights of input variables use the regression coefficient and coefficient of determination. To verify the effectiveness of the new model, we evaluate the efficiency of the Regional Corporations in Korea. Accordance with statistical analysis, it proved that there is no difference between the efficiency value of the DEA-AR using AHP and our DEA-AR model. Our model can be applied to a lot of research by substituting DEA-AR model relying on AHP in the future.

• Journal of the East Asian Society of Dietary Life
• /
• v.17 no.6
• /
• pp.963-971
• /
• 2007

This research aimed to determine the relationship between hotel restaurants' SCM activities and their results. The samples are included exclusive high-end hotels located in the seoul area. To analyze the data, frequency analysis, reliability analysis, factor analysis, and regression analysis were applied. Multiple regression analysis showed that SCM activities (${\beta}$=.342, p<.000), information sharing (${\beta}$=.136, p<.006), and cooperative activities (${\beta}$=.120, p<.015) had a significant impact on financial performance. The explanatory power of this model was 14%, and there was statistical significance in the regression model. SCM activities(${\beta}$=.221, p<.000), information sharing (${\beta}$=.475, p<.000), and cooperative activities (${\beta}$=.172, p<.000) also had a significant impact on non-financial performance, and the explanatory power of this model was 29%, with statistical significance in the regression model.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.11 no.6
• /
• pp.69-74
• /
• 2012

Surface roughness is widely used as an index for processing degree of accuracy. Recently, regression analysis to predict the machining results are actively used to characterize a cutting operations. In the past, diamond machining had been used for ultra precision cutting operation, but now industrial diamond tools like PCD(Polycrystalline Diamond) have been widely used in ultraprecision machining of nonferrous metals. In this study, the authors focus on the effect of PCD tool property on the surface roughness of Al5083 aluminum alloy after cutting process by CNC operated lathe. Based on the regression analysis approach on a surface roughness data obtained by experiment, predictive analysis of surface roughness is effective to achieve better surface quality.

• Journal of Aerospace System Engineering
• /
• v.7 no.4
• /
• pp.1-11
• /
• 2013

In this study, probabilistic reliability analysis was conducted for hybrid rocket performance using Monte-Carlo Simulation. For the accuracy, reliability analysis was performed with experimental data. To simplify the analysis process, the oxidizer was supplied with constant pressure, so that pressure variation with time can be eliminated. And time-space averaged regression rate model was used. The regression rate is obtained with a series of experiments. For reliability analysis of thrust, constant exponent of regression rate is assumed that has probabilistic character. So, the efficiency of characteristic velocity has also probabilistic values. As a results, probability distribution of the thrust is obtained by Monte-Carlo simulation using random samples of the input parameter and validated under the 95% confidence level.