Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Korean Journal of Applied Statistics
Journal Basic Information
Journal DOI :
The Korean Statistical Society
Editor in Chief :
Volume & Issues
Volume 24, Issue 6 - Dec 2011
Volume 24, Issue 5 - Oct 2011
Volume 24, Issue 4 - Aug 2011
Volume 24, Issue 3 - Jun 2011
Volume 24, Issue 2 - Apr 2011
Volume 24, Issue 1 - Feb 2011
Selecting the target year
Logistic Regression Type Small Area Estimations Based on Relative Error
Hwang, Hee-Jin ; Shin, Key-Il ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 445~453
DOI : 10.5351/KJAS.2011.24.3.445
Almost all small area estimations are obtained by minimizing the mean squared error. Recently relative error prediction methods have been developed and adapted to small area estimation. Usually the estimators obtained by using relative error prediction is called a shrinkage estimator. Especially when data set consists of large range values, the shrinkage estimator is known as having good statistical properties and an easy interpretation. In this paper we study the shrinkage estimators based on logistic regression type estimators for small area estimation. Some simulation studies are performed and the Economically Active Population Survey data of 2005 is used for comparison.
An Analysis of the Relationship between Domestic and Overseas Investment Using a Regression Tree
Chang, Young-Jae ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 455~464
DOI : 10.5351/KJAS.2011.24.3.455
Overseas direct investment is constantly on the rise, while domestic investment has been slowing and has led to concerns that the expansion of overseas investment may be weakening domestic investment. Considering the change of environment as economic growth, this paper analyzes the relationship between domestic and overseas investment using a regression tree. The result shows that overseas investment substituted domestic investment in the past (before 1985); however, they compensated for each other during the rapid growth period based on exports (1986-1997). The relationship turns out to be insignificant after the Asian currency crisis(after 1998). In addition, this paper also examines the factors determining domestic facilities investment and overseas direct investment at each stage of the changes in their influence due to globalization. Taking into account the results, we need to re-evaluate the current pattern of corporate investment apart from the past restricted point of view to help domestic enterprises efficiently utilize the international production network and resources.
Forecasting the Demand Areas of a Factory Site: Based on a Statistical Model and Sampling Survey
Jeong, Hyeong-Chul ; Han, Geun-Shik ; Kim, Seong-Yong ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 465~475
DOI : 10.5351/KJAS.2011.24.3.465
In this paper, we have considered the problems of the estimation of the gross areas of a factory site relating to the areas of industrial complex lands based on a statistical forecasting model and the results of a sampling survey. In respect to the data of a gross areas of a factory site, we have only the sizes from 1981-2003. In 2009, the Korea Industrial Complex Corp. conducted a sampling survey to estimate its bulk size, and investigate the demands of its sizes for the next five years. In this study, we have adopted the sampling survey results, and have created a statistical growth model for the gross areas of a factory site to improve the prediction for the areas of a factory site. The three-different parts of data: the results of areas of a factory site by Korea National Statistical Office, imputation results by the statistical forecasting model, and sampling survey results have used as the basis for analysis. The combination of the three-different parts of data has created a new forecasting value of the areas of a factory site through the spline smoothing method.
A Study on the Adjustment of Posterior Probability for Oversampling when the Target is Rare
Kim, U.N. ; Lee, S.K. ; Choi, J.H. ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 477~484
DOI : 10.5351/KJAS.2011.24.3.477
When an event of target variable is rare, a widespread strategy is to build a model on the sample that disproportionally over-represents the events, that is over-sampled. Using the data over-sampled from the original data set, the predicted values would be biased; however, it can be easily corrected to represent the population. In this study, we investigate into the relationship between the proportion of rare event on a data-mart and the model performance using real world data of a Korean credit card company. Also, we use the methods for adjusting of posterior probability for over-sampled data of the offset method and the weighted method. Finally, we compare the performance of the methods using real data sets.
A Zero-Inated Model for Insurance Data
Choi, Jong-Hoo ; Ko, In-Mi ; Cheon, Soo-Young ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 485~494
DOI : 10.5351/KJAS.2011.24.3.485
When the observations can take only the non-negative integer values, it is called the count data such as the numbers of car accidents, earthquakes, or insurance coverage. In general, the Poisson regression model has been used to model these count data; however, this model has a weakness in that it is restricted by the equality of the mean and the variance. On the other hand, the count data often tend to be too dispersed to allow the use of the Poisson model in practice because the variance of data is significantly larger than its mean due to heterogeneity within groups. When overdispersion is not taken into account, it is expected that the resulting parameter estimates or standard errors will be inefficient. Since coverage is the main issue for insurance, some accidents may not be covered by insurance, and the number covered by insurance may be zero. This paper considers the zero-inflated model for the count data including many zeros. The performance of this model has been investigated by using of real data with overdispersion and many zeros. The results indicate that the Zero-Inflated Negative Binomial Regression Model performs the best for model evaluation.
Statistical Considerations in the Design of Biosimilar Cancer Clinical Trials
Ahn, Chul ; Lee, Seung-Chun ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 495~503
DOI : 10.5351/KJAS.2011.24.3.495
When a patent of an innovative (brand-name) small-molecule drug expires, generic copies of the innovative drug may be marketed if their therapeutic equivalence to the innovative drug has been shown. The small-molecule drugs are considered therapeutically equivalent and can be used interchangeably if two drugs are shown to be pharmaceutically equivalent with identical active substance and bioequivalent with comparable pharmacokinetics in a crossover clinical trial. However, the therapeutic equivalence paradigm cannot be applied to biosimilars since the active ingredients of biosimilars are huge molecules with complex and heterogeneous structures, and these molecules are difficult to replicate in every detail. The European Medicine Agency(EMEA) has introduced a regulatory biosimilar pathway which mandates clinical trials to show therapeutic equivalence. In this paper, we discuss statistical considerations in the design and analysis of biosimilar cancer clinical trials.
Orthogonal Sudoku Square Designs with Block Effect Discrimination
Jang, Dae-Heung ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 505~513
DOI : 10.5351/KJAS.2011.24.3.505
Sudoku is a famous Latin-square-based number-placement puzzle. Mo and Xu (2008) proposed Sudoku square designs based on the idea of Sudoku. Using several Sudoku square designs which are mutually orthogonal, we can suggest the orthogonal Sudoku square designs with block effect discrimination.
Reliability Analysis of Repairable Systems Considering Failure Detection Equipments
Na, Seong-Ryong ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 515~521
DOI : 10.5351/KJAS.2011.24.3.515
In this paper we consider failure detection equipment that which find failures in repairable systems and enable repair operations. In practical situations, failure detection equipment may come across troubles that can cause the omissions in detecting system failures and have a serious effect on system reliability. We analyze this effect through the appropriate modeling of Markov processes.
VaR Estimation of Multivariate Distribution Using Copula Functions
Hong, Chong-Sun ; Lee, Jae-Hyung ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 523~533
DOI : 10.5351/KJAS.2011.24.3.523
Most nancial preference methods for market risk management are to estimate VaR. In many real cases, it happens to obtain the VaRs of the univariate as well as multivariate distributions based on multivariate data. Copula functions are used to explore the dependence of non-normal random variables and generate the corresponding multivariate distribution functions in this work. We estimate Archimedian Copula functions including Clayton Copula, Gumbel Copula, Frank Copula that are tted to the multivariate earning rate distribution, and then obtain their VaRs. With these Copula functions, we estimate the VaRs of both a certain integrated industry and individual industries. The parameters of three kinds of Copula functions are estimated for an illustrated stock data of two Korean industries to obtain the VaR of the bivariate distribution and those of the corresponding univariate distributions. These VaRs are compared with those obtained from other methods to discuss the accuracy of the estimations.
Binary Forecast of Asian Dust Days over South Korea in the Winter Season
Sohn, Keon-Tae ; Lee, Hyo-Jin ; Kim, Seung-Bum ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 535~546
DOI : 10.5351/KJAS.2011.24.3.535
This study develops statistical models for the binary forecast of Asian dust days over South Korea in the winter season. For this study, we used three kinds of data; the rst one is the observed Asian dust days for a period of 31 years (1980 to 2010) as target values, the second one is four meteorological factors(near surface temperature, precipitation, snowfall, ground wind speed) in the source regions of Asian dust based on the NCEP reanalysis data and the third one is the large-scale climate indices. Four kinds of statistical models(multiple regression models, logistic regression models, decision trees, and support vector machines) are applied and compared based on skill scores(hit rate, probability of detection and false alarm rate).
Modeling on Daily Traffic Volume of Local State Road Using Circular Mixture Distributions
Na, Jong-Hwa ; Jang, Young-Mi ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 547~557
DOI : 10.5351/KJAS.2011.24.3.547
In this paper we developed a statistical model for traffic volume data which collected from a spot of specific local state road. One peculiar property of daily traffic data is that it has bimodal shape which have two peaks on times of both going to office and coming back to home. So, various mixture models of circular distribution are suggested for bimodal traffic data and EM algorithms are applied to estimate the parameters of the suggested models. To compare the accuracy of the suggested models, classical regressions with dummy variables are also considered. The suggested models for traffic volumn data can be effectively used to estimate missing values due to measuring instrument disorder.
Partial Canonical Correlation Biplot
Yeom, Ah-Rim ; Choi, Yong-Seok ;
Korean Journal of Applied Statistics, volume 24, issue 3, 2011, Pages 559~566
DOI : 10.5351/KJAS.2011.24.3.559
Biplot is a useful graphical method to explore simultaneously rows and columns of two-way data matrix. In particular, canonical correlation biplot is a method for investigating two sets of variables and observations in canonical correlation analysis graphically. For more than three sets of variables, we can apply the generalized canonical correlation biplot in generalized canonical correlation analysis which is an expansion of the canonical correlation analysis. On the other hand, we consider the set of covariate variables which is affecting the linearly two sets of variables. In this case, if we apply the generalized canonical correlation biplot, we cannot clearly interpret the other two sets of variables due to the effect of the set of covariate variables. Therefor, in this paper, we will apply the partial canonical correlation analysis of Rao (1969) removing the linear effect of the set of covariate variables on two sets of variables. We will suggest the partial canonical correlation biplot for inpreting the partial canonical correlation analysis graphically.