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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Communications for Statistical Applications and Methods
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Journal DOI :
The Korean Statistical Society
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Volume & Issues
Volume 15, Issue 6 - Nov 2008
Volume 15, Issue 5 - Sep 2008
Volume 15, Issue 4 - Jul 2008
Volume 15, Issue 3 - May 2008
Volume 15, Issue 2 - Mar 2008
Volume 15, Issue 1 - Jan 2008
Selecting the target year
Speedup of EM Algorithm by Binning Data for Normal Mixtures
Oh, Chang-Hyuck ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 1~11
DOI : 10.5351/CKSS.2008.15.1.001
For a large data set the high computational cost of estimating the parameters of normal mixtures with the conventional EM algorithm is crucially impedimental in applying the algorithm to the areas requiring high speed computation such as real-time speech recognition. Simulations show that the binned EM algorithm, being compared to the standard one, significantly reduces the cost of computation without loss in accuracy of the final estimates.
Multiple Comparison for the One-Way ANOVA with the Power Prior
Bae, Re-Na ; Kang, Yun-Hee ; Hong, Min-Young ; Kim, Seong-W. ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 13~26
DOI : 10.5351/CKSS.2008.15.1.013
Inference on the present data will be more reliable when the data arising from previous similar studies are available. The data arising from previous studies are referred as historical data. The power prior is defined by the likelihood function based on the historical data to the power
. The power prior is a useful informative prior for Bayesian inference such as model selection and model comparison. We utilize the historical data to perform multiple comparison in the one-way ANOVA model. We demonstrate our results with some simulated datasets under a simple order restriction between the treatments.
A Graphical Method of Checking the Adequacy of Linear Systematic Component in Generalized Linear Models
Kim, Ji-Hyun ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 27~41
DOI : 10.5351/CKSS.2008.15.1.027
A graphical method of checking the adequacy of a generalized linear model is proposed. The graph helps to assess the assumption that the link function of mean can be expressed as a linear combination of explanatory variables in the generalized linear model. For the graph the boosting technique is applied to estimate nonparametrically the relationship between the link function of the mean and the explanatory variables, though any other nonparametric regression methods can be applied. Through simulation studies with normal and binary data, the effectiveness of the graph is demonstrated. And we list some limitations and technical details of the graph.
Sparse Multinomial Kernel Logistic Regression
Shim, Joo-Yong ; Bae, Jong-Sig ; Hwang, Chang-Ha ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 43~50
DOI : 10.5351/CKSS.2008.15.1.043
Multinomial logistic regression is a well known multiclass classification method in the field of statistical learning. More recently, the development of sparse multinomial logistic regression model has found application in microarray classification, where explicit identification of the most informative observations is of value. In this paper, we propose a sparse multinomial kernel logistic regression model, in which the sparsity arises from the use of a Laplacian prior and a fast exact algorithm is derived by employing a bound optimization approach. Experimental results are then presented to indicate the performance of the proposed procedure.
Access to Databases through the R-Language
Sim, Song-Yong ; Kang, Hee-Mo ; Lee, Yoon-Hwan ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 51~64
DOI : 10.5351/CKSS.2008.15.1.051
In general, R is useful for small size data. We study how to access a large data set in a database by R-language. We provide real examples to access data sets stored in database servers MySQL, Oracle or PostgreSQL.
Applications of Cluster Analysis in Biplots
Choi, Yong-Seok ; Kim, Hyoung-Young ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 65~76
DOI : 10.5351/CKSS.2008.15.1.065
Biplots are the multivariate analogue of scatter plots. They approximate the multivariate distribution of a sample in a few dimensions, typically two, and they superimpose on this display representations of the variables on which the samples are measured(Gower and Hand, 1996, Chapter 1). And the relationships between the observations and variables can be easily seen. Thus, biplots are useful for giving a graphical description of the data. However, this method does not give some concise interpretations between variables and observations when the number of observations are large. Therefore, in this study, we will suggest to interpret the biplot analysis by applying the K-means clustering analysis. It shows that the relationships between the clusters and variables can be easily interpreted. So, this method is more useful for giving a graphical description of the data than using raw data.
PM Policy with Random Maintenance Quality Following the Expiration of Non-Renewing Warranty
Jung, Ki-Mun ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 77~86
DOI : 10.5351/CKSS.2008.15.1.077
This paper develops the optimal periodic preventive maintenance policy following the expiration of non-renewing warranty. We assume that Wu and Clements-Croome`s (2005) periodic PM model with random maintenance quality is utilized to maintain the system after the non-renewing warranty is expired. Given the cost structure to the user during the cycle of the product, we drive the expressions for the expected cost rate per unit time. Also, we obtain the optimal number and the optimal period by minimizing the expected cost rate per unit time. The numerical examples are presented for illustrative purpose.
Andrews` Plots for Extended Uses
Kwak, Il-Youp ; Huh, Myung-Hoe ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 87~94
DOI : 10.5351/CKSS.2008.15.1.087
Andrews (1972) proposed to combine trigonometric functions to represent n observations of p variates, where the coefficients in linear sums are taken from the values of corresponding observation`s respective variates. By viewing Andrews` plot as a collection of n trajectories of p-dimensional objects (observations) as a weighting point loaded with dimensional weights moves along a certain path on the hyper-dimensional sphere, we develop graphical techniques for further uses in data visualization. Specifically, we show that the parallel coordinate plot is a special case of Andrews` plot and we demonstrate the versatility of Andrews` plot with a projection pursuit engine.
Minimizing Weighted Mean of Inefficiency for Robust Designs
Seo, Han-Son ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 95~104
DOI : 10.5351/CKSS.2008.15.1.095
This paper addresses issues of robustness in Bayesian optimal design. We may have difficulty applying Bayesian optimal design principles because of the uncertainty of prior distribution. When there are several plausible prior distributions and the efficiency of a design depends on the unknown prior distribution, robustness with respect to misspecification of prior distribution is required. We suggest a new optimal design criterion which has relatively high efficiencies across the class of plausible prior distributions. The criterion is applied to the problem of estimating the turning point of a quadratic regression, and both analytic and numerical results are shown to demonstrate its robustness.
Application of Judgement Post-Stratification to Extended Producer Responsibility System
Choi, Wan-Suk ; Lim, Jo-Han ; Lim, Jong-Ho ; Kim, Hyun-Joong ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 105~115
DOI : 10.5351/CKSS.2008.15.1.105
Judgement post-stratification is a new sampling method developed by MacEachern et al. (2004). This article suggests that the judgement post-stratification method can be a good alternative for the simple random sampling when analyzing real-world environmental data. It becomes an important task to accurately measure the output of a recycling facility since the EPR (Extended Producer Responsibility) system takes effect on 2003. However, the total weight of materials processed in the recycling facility may not be a proper measure because the materials are frequently mingled with other non-recycling materials. Therefore, it is necessary to estimate the mixture ratio of non-recycling materials among the total materials admitted in the facility. Unfortunately, the size of sample in a recycling facility is restricted due to the inconvenience of sampling procedure such as safety, odor, time and classification of non-recycling materials. In this article, we showed the relative efficiency of the judgement post-stratification method over the simple random sampling method for equal sample sizes using Monte Carlo simulation. Furthermore, we applied the judgement post-stratification method on the 2004 recycling data and showed that it can replace the simple random sampling even with smaller observations.
Estimation of Liquidity Cost in Financial Markets
Lim, Jo-Han ; Lee, Ki-Seop ; Song, Hyun-Seok ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 117~124
DOI : 10.5351/CKSS.2008.15.1.117
The liquidity risk is defined as an additional risk in the market due to the timing and size of a trade. A recent work by Cetin et ai. (2003) proposes a rigorous mathematical model incorporating this liquidity risk into the arbitrage pricing theory. A practical problem arising in a real market application is an estimation problem of a liquidity cost. In this paper, we propose to estimate the liquidity cost function in the context of Cetin et al. (2003) using the constrained least square (LS) method, and illustrate it by analyzing the Kellogg company data.
Using Support Vector Regression for Optimization of Black-box Objective Functions
Kwak, Min-Jung ; Yoon, Min ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 125~136
DOI : 10.5351/CKSS.2008.15.1.125
In many practical engineering design problems, the form of objective functions is not given explicitly in terms of design variables. Given the value of design variables, under this circumstance, the value of objective functions is obtained by real/computational experiments such as structural analysis, fluid mechanic analysis, thermodynamic analysis, and so on. These experiments are, in general, considerably expensive. In order to make the number of these experiments as few as possible, optimization is performed in parallel with predicting the form of objective functions. Response Surface Methods (RSM) are well known along this approach. This paper suggests to apply Support Vector Machines (SVM) for predicting the objective functions. One of most important tasks in this approach is to allocate sample data moderately in order to make the number of experiments as small as possible. It will be shown that the information of support vector can be used effectively to this aim. The effectiveness of our suggested method will be shown through numerical example which is well known in design of engineering.
Cap Pricings under the Fractional Brownian Motion
Rhee, Joon-Hee ; Kim, Yoon-Tae ;
Communications for Statistical Applications and Methods, volume 15, issue 1, 2008, Pages 137~145
DOI : 10.5351/CKSS.2008.15.1.137
We present formulas for two types of cap pricing under fBm-HJM model reflecting the empirical long range dependence in the interest rate model. In particular, we propose a new approach to pricing the cap with the default risk.