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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Applied Statistics
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Journal DOI :
The Korean Statistical Society
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Volume & Issues
Volume 27, Issue 7 - Dec 2014
Volume 27, Issue 6 - Dec 2014
Volume 27, Issue 5 - Oct 2014
Volume 27, Issue 4 - Aug 2014
Volume 27, Issue 3 - Jun 2014
Volume 27, Issue 2 - Apr 2014
Volume 27, Issue 1 - Feb 2014
Selecting the target year
Decision of Sample Size on Successive Occasions
Park, Hyeonah ; Na, Seongryong ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 513~521
DOI : 10.5351/KJAS.2014.27.4.513
If the target error of an estimator at the present time is greater than the coefficient of variation(CV) of the estimator at the previous time, sample size at this point should be decreased. Various papers have researched sample size determination methods using the CV of an estimator at the previous time, variation of population size and target error of the estimator at this time in sampling on successive occasions. We research a new sample size determination method additionally using change of population CV. We compare the proposed method with existing ones in various simulation settings.
The Analysis of Roll Call Data from the 18th Korean National Assembly: A Bayesian Approach
Hahn, Kyu S. ; Kim, Yuneung ; Lim, Jongho ; Lim, Johan ; Kwon, Suhyun ; Lee, Kyeong Eun ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 523~541
DOI : 10.5351/KJAS.2014.27.4.523
We apply a Bayesian estimation procedure to the analysis of roll call voting records on 2,389 bills processed during the 18th Korean National Assembly. The analysis of roll calls yields useful tools for to combining the measurement of legislative preference with the models of legislative behavior. The current Bayesian procedure is extremely exible, applicable to any legislative setting, irrespective of the extremism of the legislator's voting history or the number of roll calls available for analysis. It can be applied to any legislative settings, providing a useful solution to many statistical problems inherent in the analysis of roll call voting records. We rst estimate the ideal points of all members of the 18th National Assembly and their condence intervals. Subsequently, using the estimated ideal points, we examine the factional disparity within each major party using the estimated ideal points. Our results clearly suggest that there exists a meaningful ideological spectrum within each party. We also show how the Bayesian procedure can easily be extended to accommodate theoretically interesting theoretical models of legislative behavior. More specically, we demonstrate how the estimated posterior probabilities can be used for identifying pivotal legislators.
Optimization for Electro Deposition Process of PC/ABS Resin Surface Treatment
Park, Young Sik ; Shim, Ha-Mong ; Na, Myung Hwan ; Song, Ho-Chun ; Yoon, Sanghoo ; Jang, Keun Sam ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 543~552
DOI : 10.5351/KJAS.2014.27.4.543
High bandwidth RF such as Bluetooth, GPRS, EDGE, 3GSM, HSDPA is papular in the mobile phone market. A non-conducting metal coating process requires an e-beam deposition of metal, two steps of UV hard coating primer and top coating; however, it is inefficient. We navigate to the electron beam irradiation conditions(resin surface treatment conditions) in the PC/ABS resin injection process. By analyzing the experimental results, we find the optimum development conditions for the electro deposition pre-treatment process and mass production lines using the plasma generated electron beam source.
Estimable Functions of Fixed-Effects Model by Projections
Choi, Jaesung ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 553~560
DOI : 10.5351/KJAS.2014.27.4.553
This paper deals with estimable functions of parameters of less than full rank linear model. In general, the parameters of an overspecified model are not uniquely determined by least squares solutions. It discusses how to formulate linear estimable functions as functions of parameters in the model and shows how to use projection matrices to check out whether a parameter or function of the pamameters is estimable. It also presents a method to form a basis set of estimable functions using linearly independent characteristic vectors generating the row space of the model matrix.
Spatial Clustering Method Via Generalized Lasso
Song, Eunjung ; Choi, Hosik ; Hwang, Seungsik ; Lee, Woojoo ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 561~575
DOI : 10.5351/KJAS.2014.27.4.561
In this paper, we propose a penalized likelihood method to detect local spatial clusters associated with disease. The key computational algorithm is based on genlasso by Tibshirani and Taylor (2011). The proposed method has two main advantages over Kulldorff's method which is popoular to detect local spatial clusters. First, it is not needed to specify a proper cluster size a priori. Second, any type of covariate can be incorporated and, it is possible to find local spatial clusters adjusted for some demographic variables. We illustrate our proposed method using tuberculosis data from Seoul.
Analyzing Financial Data from Banks and Savings Banks: Application of Bioinformatical Methods
Pak, Ro Jin ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 577~588
DOI : 10.5351/KJAS.2014.27.4.577
The collection and storage of a large volumes of data are becoming easier; however, the number of variables is sometimes more than the number of samples(objects). We now face the problem of dependency among variables(such as multicollinearity) due to the increased number of variables. We cannot apply various statistical methods without satisfying independency assumption. In order to overcome such a drawback we consider a categorizing (or discretizing) observations. We have a data set of nancial indices from banks in Korea that contain 78 variables from 16 banks. Genetic sequence data is also a good example of a large data and there have been numerous statistical methods to handle it. We discover lots of useful bank information after we transform bank data into categorical data that resembles genetic sequence data and apply bioinformatic techniques.
Bayesian Detection of Multiple Change Points in a Piecewise Linear Function
Kim, Joungyoun ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 589~603
DOI : 10.5351/KJAS.2014.27.4.589
When consecutive data follows different distributions(depending on the time interval) change-point detection infers where the changes occur first and then finds further inferences for each sub-interval. In this paper, we investigate the Bayesian detection of multiple change points. Utilizing the reversible jump MCMC, we can explore parameter spaces with unknown dimensions. In particular, we consider a model where the signal is a piecewise linear function. For the Bayesian inference, we propose a new Bayesian structure and build our own MCMC algorithm. Through the simulation study and the real data analysis, we verified the performance of our method.
Shrinkage Small Area Estimation Using a Semiparametric Mixed Model
Jeong, Seok-Oh ; Choo, Manho ; Shin, Key-Il ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 605~617
DOI : 10.5351/KJAS.2014.27.4.605
Small area estimation is a statistical inference method to overcome large variance due to a small sample size allocated in a small area. A shrinkage estimator obtained by minimizing relative error(RE) instead of MSE has been suggested. The estimator takes advantage of good interpretation when the data range is large. A semiparametric estimator is also studied for small area estimation. In this study, we suggest a semiparametric shrinkage small area estimator and compare small area estimators using labor statistics.
Visualizations of Asymmetric Multidimensional Scaling
Lee, Su-Gi ; Choi, Yong-Seok ; Lee, Bo-Hui ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 619~627
DOI : 10.5351/KJAS.2014.27.4.619
Distances or dissimilarities among units are assumed to be symmetric in most cases of multidimensional scaling(MDS); consequently, it is not an easy task to deal with asymmetric distances. Current asymmetric MDS still face difficulties in the interpretation of results. This study proposes a simpler asymmetric MDS that utilizes the order statistic of an asymmetric matrix. The proposed Web method demonstrates that some influences among objects are visualized by direction, size and shape of arrow to ease the interpretability of users.
Firework Plot as a Graphical Exploratory Data Analysis Tool to Evaluate the Impact of Outliers in a Mixture Experiment
Jang, Dae-Heung ; Ahn, SoJin ; Kim, Youngil ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 629~643
DOI : 10.5351/KJAS.2014.27.4.629
It is common to check the validity of an assumed model with the heavy use of diagnostics tools when conducting data analysis with regression techniques; however, outliers and influential data points often distort the regression output in undesired manner. Jang and Anderson-Cook (2013) proposed a graphical method called a firework plot for exploratory analysis that could visualize the trace of the impact of possible outlying and/or influential data points on individual regression coefficients and the overall residual sum of squares(SSE) measure. They developed 3-D plot as well as pair-wise plot for the appropriate measures of interest. In this paper, the approach was extended further to tell the strength of their approach; in addition, a more meaningful interpretation was possible by adding a measure not mentioned in their paper. This approach was applied to the mixture experiment because we felt that a detailed analysis of statistical measure sensitivity is required in a small experiment.
Reproducibility of Hypothesis Testing and Confidence Interval
Huh, Myung-Hoe ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 645~653
DOI : 10.5351/KJAS.2014.27.4.645
P-value is the probability of observing a current sample and possibly other samples departing equally or more extremely from the null hypothesis toward postulated alternative hypothesis. When p-value is less than a certain level called
(= 0:05), researchers claim that the alternative hypothesis is supported empirically. Unfortunately, some findings discovered in that way are not reproducible, partly because the p-value itself is a statistic vulnerable to random variation. Boos and Stefanski (2011) suggests calculating the upper limit of p-value in hypothesis testing, using a bootstrap predictive distribution. To determine the sample size of a replication study, this study proposes thought experiments by simulating boosted bootstrap samples of different sizes from given observations. The method is illustrated for the cases of two-group comparison and multiple linear regression. This study also addresses the reproducibility of the points in the given 95% confidence interval. Numerical examples show that the center point is covered by 95% confidence intervals generated from bootstrap resamples. However, end points are covered with a 50% chance. Hence this study draws the graph of the reproducibility rate for each parameter in the confidence interval.
Threshold Modelling of Spatial Extremes - Summer Rainfall of Korea
Hwang, Seungyong ; Choi, Hyemi ;
Korean Journal of Applied Statistics, volume 27, issue 4, 2014, Pages 655~665
DOI : 10.5351/KJAS.2014.27.4.655
An adequate understanding and response to natural hazards such as heat wave, heavy rainfall and severe drought is required. We apply extreme value theory to analyze these abnormal weather phenomena. It is common for extremes in climatic data to be nonstationary in space and time. In this paper, we analyze summer rainfall data in South Korea using exceedance values over thresholds estimated by quantile regression with location information and time as covariates. We group weather stations in South Korea into 5 clusters and t extreme value models to threshold exceedances for each cluster under the assumption of independence in space and time as well as estimates of uncertainty for spatial dependence as proposed in Northrop and Jonathan (2011).