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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Applied Statistics
Journal Basic Information
Journal DOI :
The Korean Statistical Society
Editor in Chief :
Volume & Issues
Volume 26, Issue 6 - Dec 2013
Volume 26, Issue 5 - Oct 2013
Volume 26, Issue 4 - Aug 2013
Volume 26, Issue 3 - Jun 2013
Volume 26, Issue 2 - Apr 2013
Volume 26, Issue 1 - Feb 2013
Selecting the target year
Time Series Models for Daily Exchange Rate Data
Kim, Bomi ; Kim, Jaehee ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 1~14
DOI : 10.5351/KJAS.2013.26.1.001
ARIMA and ARIMA+IGARCH models are fitted and compared for daily Korean won/US dollar exchange rate data over 17 years. A linear structural change model and an autoregressive structural change model are fitted for multiple change-point estimation since there seems to be structural change with this data.
The Effect Measures for Diagnostic Test: A Graph Approach
Cho, Tae-Kyoung ; Son, Chang-Kyoon ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 15~22
DOI : 10.5351/KJAS.2013.26.1.015
In clinical study or epidemic research, the
frequency table is useful to present a summary statistic The values of four cells in
table use to calculate the effect measures such as risk ratio, relative ris ratio or odds ratio. In this paper, we suggest that the improved visualization method using a radar diagram supported by MS-office Excel from the
frequency table is able to understand and draw easily betweendiagnosti measures such as sensitivity, specificity, predictivity, and likelihood ratio. We use some numerical example in order to show the usage of the proposed method.
Analysis to Customer Churn Provoker's Roles Using Call Network of a Telecom Company
Chun, Heuiju ; Leem, Byunghak ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 23~36
DOI : 10.5351/KJAS.2013.26.1.023
In this study, we investigate how churn customers (who play a central connector or broker role) affect other customers' churn in their call networks with ego-network analysis using call data of a mobile telecom company in Korea. As a result of investigating Reciprocal Network, we found a relationship of attrition among churn customers. Churn provokers who influence other customers' attrition exist in customer churn networks. The characteristics of churn provokers is that they play a central connector and broker role in their groups. The proportion of churn provokers increases and the churn provoker's influence increases because the network is a reciprocal one.
A Graphical Method to Assess Goodness-of-Fit for Inverse Gaussian Distribution
Choi, Byungjin ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 37~47
DOI : 10.5351/KJAS.2013.26.1.037
A Q-Q plot is an effective and convenient graphical method to assess a distributional assumption of data. The primary step in the construction of a Q-Q plot is to obtain a closed-form expression to represent the relation between observed quantiles and theoretical quantiles to be plotted in order that the points fall near the line y = a + bx. In this paper, we introduce a Q-Q plot to assess goodness-of-fit for inverse Gaussian distribution. The procedure is based on the distributional result that a transformed random variable
follows a half-normal distribution with mean 0 and variance 1 when a random variable X has an inverse Gaussian distribution with location parameter
and scale parameter
. Simulations are performed to provide a guideline to interpret the pattern of points on the proposed inverse Gaussian Q-Q plot. An illustrative example is provided to show the usefulness of the inverse Gaussian Q-Q plot.
Evaluating the Operational Efficiencies of Local Universities Using DEA Approach
Choi, Kyoung Ho ; Ahn, Jeong Yong ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 49~58
DOI : 10.5351/KJAS.2013.26.1.049
Data envelopment analysis is a relatively new data oriented approach to evaluate the performance of a set of peer entities called decision making units which convert multiple inputs into multiple outputs. It has been extensively applied in performance evaluation and benchmarking entities such as hospitals, universities, cities, courts, and business firms. This study provides the evaluating results of the operational efficiencies of local universities using a DEA approach. In addition, we explore the difference of the efficiency between regional flagship national universities and non-flagships.
Estimating the Number of Seats in Local Constituencies of a Party Using Exit Polls in the General Election
Kim, Ji-Hyun ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 59~70
DOI : 10.5351/KJAS.2013.26.1.059
Exit polls failed to estimate the number of seats in the National Assembly for each party in the 2012 General Election, even though they estimated it in interval. Three major broadcast companies jointly carried out exit polls, but made projections independently. The exact methods of projection were not publicly released. This paper proposes confidence intervals for the number of seats in local constituencies using the results of exit polls, and conducted simulation studies to assess the performance of the cofidence intervals. The proposed confidence intervals were applied to the real data of 2012 General Election.
Semiparametric and Nonparametric Mixed Effects Models for Small Area Estimation
Jeong, Seok-Oh ; Shin, Key-Il ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 71~79
DOI : 10.5351/KJAS.2013.26.1.071
Semiparametric and nonparametric small area estimations have been studied to overcome a large variance due to a small sample size allocated in a small area. In this study, we investigate semiparametric and nonparametric mixed effect small area estimators using penalized spline and kernel smoothing methods respectively and compare their performances using labor statistics.
A New Statistical Index for Detecting Cheaters on Multiple Choice Tests
Han, Eun Su ; Lim, Johan ; Lee, Kyeong Eun ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 81~92
DOI : 10.5351/KJAS.2013.26.1.081
It is important to construct a firm basis for accusing potential violators of academic integrity in order to avoid spurious accusations and false convictions. Educational researchers have developed many statistical methods that can either uncover or confirm cases of cheating on tests. However, most of them rely on simple correlation-based measures, and often fail to account for patterns in responses or answers. In this paper, we propose a new statistical index denoted by a Standardized Signed Entropy Similarity Score to resolve this difficulty. In addition, we apply the proposed method to analyze a real data set and compare the results to other existing methods.
On the Hierarchical Modeling of Spatial Measurements from Different Station Networks
Choi, Jieun ; Park, Man Sik ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 93~109
DOI : 10.5351/KJAS.2013.26.1.093
Geostatistical data or point-referenced data have the information on the monitoring stations of interest where the observations are measured. Practical geostatistical data are obtained from a wide variety of observational monitoring networks that are mainly operated by the Korean government. When we analyze geostatistical data and predict the expectations at unobservable locations, we can improve the reliability of the prediction by utilizing some relevant spatial data obtained from different observational monitoring networks and blend them with the measurements of our main interest. In this paper, we consider the hierarchical spatial linear model that enables us to link spatial variables from different resources but with similar patterns and guarantee the precision of the prediction. We compare the proposed model to a classical linear regression model and simple kriging in terms of some information criteria and one-leave-out cross-validation. Real application deals with Sulfur Dioxide(
) measurements from the urban air pollution monitoring network and wind speed data from the surface observation network.
The Effect of Failure Detection Equipment on System Availability
Na, Seongryong ; Bang, Sung-Hwan ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 111~118
DOI : 10.5351/KJAS.2013.26.1.111
In this paper we study the effect of failure detection equipment(FDE)s on system availability. A new repair scheme is considered for the step of repairing FDE which becomes out of order in the course of repairing the main system(MS). We compute and compare the availability of MS.
Study on the Efficiency of Multi-State κ-out-of-n System
Kim, Jihyun ; Nam, Hae Byur ; Cha, Ji Hwan ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 119~130
DOI : 10.5351/KJAS.2013.26.1.119
A system with
components which functions when at least
of the components function is called
system. Most studies on
system derive the system reliability based on the assumption that the system has just two states: functioning or failed. However, the system efficiency may depend on the number of functioning components. This paper considers a Multi-state
system and derives the total system efficiency. In addition, assuming that the system is repairable, the optimal repair policy to maximize the system efficiency is studied. The system efficiency considered in this paper can be regarded as a generalized measure of the mean time to the failure of the system.
Comparison of Feature Selection Methods in Support Vector Machines
Kim, Kwangsu ; Park, Changyi ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 131~139
DOI : 10.5351/KJAS.2013.26.1.131
Support vector machines(SVM) may perform poorly in the presence of noise variables; in addition, it is difficult to identify the importance of each variable in the resulting classifier. A feature selection can improve the interpretability and the accuracy of SVM. Most existing studies concern feature selection in the linear SVM through penalty functions yielding sparse solutions. Note that one usually adopts nonlinear kernels for the accuracy of classification in practice. Hence feature selection is still desirable for nonlinear SVMs. In this paper, we compare the performances of nonlinear feature selection methods such as component selection and smoothing operator(COSSO) and kernel iterative feature extraction(KNIFE) on simulated and real data sets.
Log-density Ratio with Two Predictors in a Logistic Regression Model
Kahng, Myung Wook ; Yoon, Jae Eun ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 141~149
DOI : 10.5351/KJAS.2013.26.1.141
We present methods for studying the log-density ratio that enables the selection of the predictors and the form to be included in the logistic regression model. Under bivariate normal distributional assumptions, we investigate the form of the log-density ratio as a function of two predictors. If two covariance matrices are equal, then the crossproduct and quadratic terms are not needed. If the variables are uncorrelated, we do not need the crossproduct terms, but we still need the linear and quadratic terms. We also explore other conditions in which the crossproduct and quadratic terms are not needed in the logistic regression model.
Optimization of Improvement Level for Second-Hand Product with Periodic Maintenance Schedule
Kim, Dae-Kyung ; Kim, Jin Woo ; Park, Dong Ho ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 151~162
DOI : 10.5351/KJAS.2013.26.1.151
Due to a growing demand for the second-hand product, especially for the expensive one, the warranty and maintenance policies for such products have been studied to improve the product reliability of late. In this paper we study a periodic maintenance model for the second-hand product which is purchased by the customer at the age of
. When purchased, the dealer provides a warranty of a fixed length during which the product is maintained periodically to reduce the failure rate of the product and thus, to improve the reliability after each maintenance is served. If a failure occurs between two successive maintenances, only minimal repair is conducted. As for the warranty policy, we adopt free non-renewing repair action on each failure, in addition to the periodic maintenance service during the warranty period. Thus, under the given warranty policy, all the maintenance and repair costs incurred during the warranty period are charged to the dealer. For the proposed periodic maintenance scheme, we formulate a cost model to evaluate the expected total cost charged to the dealer during the warranty period and derive an optimal upgrade level of the failure rate at each maintenance to minimize the expected total warranty cost from the perspective of the dealer. We also present numerical results for an optimal upgrade level based on the proposed methods.
Value-at-Risk Estimation of the KOSPI Returns by Employing Long-Memory Volatility Models
Oh, Jeongjun ; Kim, Sunggon ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 163~185
DOI : 10.5351/KJAS.2013.26.1.163
In this paper, we investigate the need to employ long-memory volatility models in terms of Value-at-Risk(VaR) estimation. We estimate the VaR of the KOSPI returns using long-memory volatility models such as FIGARCH and FIEGARCH; in addition, via back-testing we compare the performance of the obtained VaR with short memory processes such as GARCH and EGARCH. Back-testing says that there exists a long-memory property in the volatility process of KOSPI returns and that it is essential to employ long-memory volatility models for the right estimation of VaR.
Study on a Hedging Volatility Depending on Path Type of Underlying Asset Prices
Koo, Jeongbon ; Song, Junmo ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 187~200
DOI : 10.5351/KJAS.2013.26.1.187
In this paper, we deal with the problem of deciding a hedging volatility for ATM plain options when we hedge those options based on geometric Brownian motion. For this, we study the relation between hedging volatility and hedge profit&loss(P&L) as well as perform Monte Carlo simulations and real data analysis to examine how differently hedge P&L is affected by the selection of hedging volatility. In conclusion, using a relatively low hedging volatility is found to be more favorable for hedge P&L when underlying asset prices are expected to be range bound; however, a relatively high volatility is found to be favorable when underlying asset prices are expected to move on a trend.
A Note on Model Selection in Mixture Experiments with Process Variables
Kim, Jung Il ;
Korean Journal of Applied Statistics, volume 26, issue 1, 2013, Pages 201~208
DOI : 10.5351/KJAS.2013.26.1.201
In this paper, we consider the mixture components-process variables model and propose a model selection strategy using MTS. This strategy is illustrated using an example that involves three mixture components and two process variables in a bread making experiment that was studied in several literatures.