• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.153-167
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• 1997

There have been many studies concerning the relationships between stock returns and volatilities. Their positive relationship is well known from the theoretical point of view, but not empirically shown. Franch, Schwert and Stambaugh [11] has empirically provided the indirect evidence of the positive relationship betwen expected stock return and expected volatility. However, their study lacks some statistical validity. This study reexamines the relationship using regression diagnostics and GARCH model from an international point of view. The empirical results fall to show the positive relationship between expected stock return and expected volaiility, which contradicts those of France, Schwert and Stambangh [1].

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.97-108
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• 2018

It has been routine practice in regression analysis to check the validity of the assumed model by the use of regression diagnostics tools. Outliers and influential observations often distort the regression output in an undesired manner. Jang and Anderson-Cook (Quality and Reliability Engineering International, 30, 1409-1425, 2014) proposed a graphical method (called a firework plot) so that there could be an exploratory visualization of the trace of the impact of the possible outliers and influential observations on individual regression coefficients and the overall residual sum of the squares measure. This paper further extends a graphical approach to a multi-response surface methodology problem.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.441-453
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• 2008

We analyzed Korean professional basketball and baseball players salary under the assumption that it depends on the personal records and contribution to the team in the previous year. We extensively used data visualization tools to check the relationship among the variables, to find outliers and to do model diagnostics. We used multiple linear regression and regression tree to fit the model and used cross-validation to find an optimal model. We check the relationship between variables carefully and chose a set of variables for the stepwise regression instead of using all variables. We found that points per game, number of assists, number of free throw successes, career are important variables for the basketball players. For the baseball pitchers, career, number of strike-outs per 9 innings, ERA, number of homeruns are important variables. For the baseball hitters, career, number of hits, FA are important variables.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.797-804
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• 2006

A development of regression model for asphalt concrete pavements using Falling Weight Deflectometer deflections is presented in this paper. A backcalculation program based on layered elastic theory was used to generate the synthetic modulus database, which was used to generate 95% confidence intervals of modulus in each layer. Using deflection basins of FWD data used in developing this procedure were collected from Pavement Management System in flexible pavements. Assumptions of back-calculation are that one is 3 layered flexible pavement structure and another is depth to bedrock is finite. It is found that difference of between 95% confidence intervals and modulus ranges of other papers does not exist. So, the data of 95% confidence intervals in each layer was used to develop multiple regression models. Multiple regression equations of each layer were established by SPSS, package of Statics analysis. These models were proved by regression diagnostics, which include case analysis, multi-collinearity analysis, influence diagnostics and analysis of variance. And these models have higher degree of coefficient of determination than 0.75. So this models were applied to predict modulus of domestic asphalt concrete pavement at FWD field test.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.14 no.1
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• pp.15-35
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• 2010

Objectives : The purpose of this study is to find out the correlation between the Vocal indicators and the 'Buzhongyiqi-Tang questionnaire' and the 'Chalder fatigue scale.' Methods : This study examined the mean value of each factor in the 'Buzhongyiqi-Tang Questionnaire,' 'Chalder fatigue scale' and the different voice indicators conducted on 81 healthy adult participants in relation to the results of the /a/ /e/ /i/ /o/ /u/ pronunciation test. Results : There was significant correlation between the pronunciation of /a/ /e/ /i/ /o/ /u/ vowels' F0 indexes and 'the Deficiency symptoms of Buzhongyiqi-Tang'. The results of the regression analysis showed the following significant findings for each pronouncing vowels: /i/ as a factor for 'the Deficiency symptoms of Buzhongyiqi-Tang'.; /a/ for 'the Consumptive fever of Buzhongyiqi-Tang'.; /i/ for 'the Vocal inflammation of Buzhongyiqi-Tang.; and /e/ as a factor of 'the Chadler physical fatigue'. Conclusions : The study showed a negative correlation between the Fundamental Frequency and the mean value of the questionnaire, which could be understood as higher the fatigue level, increased level of vocal vibration and higher pitch tone compared to the less fatigued group. We expect future studies to conduct research on methods to diagnose other illnesses using the vocal indicators based on the correlation between the vocal index and illnesses prescribed under traditional oriental medicine.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.15 no.2
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• pp.191-202
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• 2011

Objectives: The questionnaires of body condition were developed to increase golf performance and to find psychological factors in junior golfer. This study was how much golf performances got improved after acupuncture treatment. Methods: October $28^{th}$, $29^{th}$ 2010 and January 2011, 130 junior golfers were taken 8 questionnaires. Sixty junior golfer of them were selected, twenty of them were taken acupuncture treatment spontaneously and forty of them were not taken it. The acupoints were K10, H3, Sp3, H7. The statistics was used paired student t-test of before and after treatment and correlates analysis for analyzing relationship with questionnaires. Results: 1. The result of reliability among questionnaires was signified. 2. About questionnaires, golf score was related with satisfied shots, to endure hungry and about digestion. (p<0.5) 3. Anxiety was related with pain in ribs, about sleep, about bowl movement and about digestion. 4. It was obtained Regression equation of 41.9 % prediction between anxiety and 4 questionnaires. 5. The result of paired T-Test, the difference was $2.45{\oplus}4.69$ between $1^{st}$ score and $2^{nd}$ score in acupuncture treated group. (p<0.05) Conclusions: This study was important to improve golf performance with Asian medicine. Further clinical research is necessary to develop more delicate analyses and questionnaires. Also through the diagnosis and corresponding treatments based on the Asian Medicine, the ways of improving golf performance should be developed.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.73-88
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• 1990

This study aims to develop a traffic accident forecasting model using the data, which are based on the past accidents in Korea. The regression analysis was used in conjuction with the variables of the traffic accidents and social behaviours. The objectives of this study are as follows; 1. The number of behicles has given a strong affect to increase the traffic accidents in Korea since a factor of vehicles has shown 86% over of total accidents. 2. The forecasting model regarding the traffic accidents, deaths and injuries, which was formulated for this study, proved to be useful in light of the results of the regression diagnostics. 3. It is expected that the traffic accidents in Korea in 1991 may take place as follows on condition that the traffic environment would worsen ; 274,000 cases of accidents with 13,600 deaths and 367,000 injuries, in 1994, 451,000 cases with 24,900 deaths and 71,500 injuries respectively.

• Journal of the Korean Data and Information Science Society
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• v.3 no.1
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• pp.1-16
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• 1992

In regression diagnostics, a number of joint influence measures based on various statistical tools have been discussed. We consider an alternate representation in terms of the predicted residual and g-leverage determined by the remaining points. By this approach, we choose the predicted residual sum of squares for the keypoints as joint influence measure and propose a new expression of it so that we can extend the single case form to the multiple case one. Furthermore we suggest a seach method for joint influence after investigating some properties of the new expression.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.155-162
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• 2017

In this paper we propose influence measures for two basic goodness-of-fit statistics, the coefficient of determination $R^2$ and test statistic F in the linear regression model using the deletion method. Some useful lemmas are provided. We also express the influence measures in terms of basic building blocks such as residual, leverage, and deviation that showed them as increasing function of residuals and a decreasing function of deviation. Further, the proposed measure reduces computational burden from O(n) to O(1). As illustrative examples, we applied the proposed measures to the stackloss data sets. We verified that deletion of one or few influential observations may result in big change in $R^2$ and F-statistic.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.583-604
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• 2017

The most popular regression model for the analysis of time-to-event data is the Cox proportional hazards model. While the model specifies a parametric relationship between the hazard function and the predictor variables, there is no specification regarding the form of the baseline hazard function. A critical assumption of the Cox model, however, is the proportional hazards assumption: when the predictor variables do not vary over time, the hazard ratio comparing any two observations is constant with respect to time. Therefore, to perform credible estimation and inference, one must first assess whether the proportional hazards assumption is reasonable. As with other regression techniques, it is also essential to examine whether appropriate functional forms of the predictor variables have been used, and whether there are any outlying or influential observations. This article reviews diagnostic methods for assessing goodness-of-fit for the Cox proportional hazards model. We illustrate these methods with a case-study using available R functions, and provide complete R code for a simulated example as a supplement.