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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 19, Issue 6 - Nov 2012
Volume 19, Issue 5 - Sep 2012
Volume 19, Issue 4 - Jul 2012
Volume 19, Issue 3 - May 2012
Volume 19, Issue 2 - Mar 2012
Volume 19, Issue 1 - Jan 2012
Selecting the target year
A Stratified Unknown Repeated Trials in Randomized Response Sampling
Singh, Housila P. ; Tarray, Tanveer Ahmad ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 751~759
DOI : 10.5351/CKSS.2012.19.6.751
This paper proposes an alternative stratified randomized response model based on the model of Singh and Joarder (1997). It is shown numerically that the proposed stratified randomized response model is more efficient than Hong et al. (1994) (under proportional allocation) and Kim and Warde (2004) (under optimum allocation).
Modelling Count Responses with Overdispersion
Jeong, Kwang Mo ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 761~770
DOI : 10.5351/CKSS.2012.19.6.761
We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.
Statistical Properties of News Coverage Data
Lim, Eunju ; Hahn, Kyu S. ; Lim, Johan ; Kim, Myungsuk ; Park, Jeongyeon ; Yoon, Jihee ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 771~780
DOI : 10.5351/CKSS.2012.19.6.771
In the current analysis, we examine news coverage data widely used in media studies. News coverage data is usually time series data to capture the volume or the tone of the news media's coverage of a topic. We first describe the distributional properties of autoregressive conditionally heteroscadestic(ARCH) effects and compare two major American newspaper's coverage of U.S.-North Korea relations. Subsequently, we propose a change point detection model and apply it to the detection of major change points in the tone of American newspaper coverage of U.S.-North Korea relations.
Nonparametric Tests for 2×2 Cross-Over Design
Gee, Kyuhoon ; Kim, Dongjae ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 781~791
DOI : 10.5351/CKSS.2012.19.6.781
Cross-over design is widely used in clinical trials for comparison studies of two kinds of drugs or medical treatments. This design has many statistical methods such as Hills-Armitage's (1979) method or Koch's (1972) method. In this paper, we propose a nonparametric test for
Cross-over design based on a two-sample test suggested by Baumgartner et al. (1998). In addition, a Monte Carlo simulation study is adapted to compare the power of the proposed methods with those of previous methods.
Hidden Truncation Normal Regression
Kim, Sungsu ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 793~798
DOI : 10.5351/CKSS.2012.19.6.793
In this paper, we propose regression methods based on the likelihood function. We assume Arnold-Beaver Skew Normal(ABSN) errors in a simple linear regression model. It was shown that the novel method performs better with an asymmetric data set compared to the usual regression model with the Gaussian errors. The utility of a novel method is demonstrated through simulation and real data sets.
Main Gene Combinations and Genotype Identification of Hanwoo Quality with SNPHarvester
Bae, Jae-Young ; Lee, Jea-Young ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 799~808
DOI : 10.5351/CKSS.2012.19.6.799
It is known that human disease and the economic traits of livestock are significantly affected by a gene combination effect rather than a single gene effect. Existing methods to study this gene combination effect have disadvantages such as heavy computing, cost and time; therefore, to overcome those drawbacks, the SNPHarvester was developed to find the main gene combinations. In this paper, we looked for gene combinations using an adjusted linear regression model. This research finds that superior gene combinations which are related to the quality of the Korean beef cattle among sets of SNPs using SNPHarvester. We also identify the superior genotypes using a decision tree that can enhance the various qualities of Korean beef among selected a SNP combination.
Negative Binomial Varying Coefficient Partially Linear Models
Kim, Young-Ju ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 809~817
DOI : 10.5351/CKSS.2012.19.6.809
We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.
Pricing Outside Lookback Options with Guaranteed Floating Strike
Lee, Hangsuck ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 819~835
DOI : 10.5351/CKSS.2012.19.6.819
A floating-strike lookback call (or put) option gives the holder the right to buy (or sell) at some percentage of the lowest (or highest) price of the underlying asset. This paper will propose an outside lookback call (or put) option that gives the holder the right to buy (or sell) one underlying asset at its guaranteed floating-strike price that is some percentage times the smaller (or the greater) of a specific guaranteed amount and the lowest (or highest) price of the other underlying asset. In addition, this paper derives explicit pricing formulas for these outside lookback options. Section 3 and Section 4 assume that the underlying assets pay no dividends. In contrast, Section 5 derives explicit pricing formulas for these options when their underlying assets pay dividends continuously at a rate proportional to their prices. Some numerical examples are also discussed.
Power Investigation of the Entropy-Based Test of Fit for Inverse Gaussian Distribution by the Information Discrimination Index
Choi, Byungjin ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 837~847
DOI : 10.5351/CKSS.2012.19.6.837
Inverse Gaussian distribution is widely used in applications to analyze and model right-skewed data. To assess the appropriateness of the distribution prior to data analysis, Mudholkar and Tian (2002) proposed an entropy-based test of fit. The test is based on the entropy power fraction(EPF) index suggested by Gokhale (1983). The simulation results report that the power of the entropy-based test is superior compared to other goodness-of-fit tests; however, this observation is based on the small-scale simulation results on the standard exponential, Weibull W(1; 2) and lognormal LN(0:5; 1) distributions. A large-scale simulation should be performed against various alternative distributions to evaluate the power of the entropy-based test; however, the use of a theoretical method is more effective to investigate the powers. In this paper, utilizing the information discrimination(ID) index defined by Ehsan et al. (1995) as a mathematical tool, we scrutinize the power of the entropy-based test. The selected alternative distributions are the gamma, Weibull and lognormal distributions, which are widely used in data analysis as an alternative to inverse Gaussian distribution. The study results are provided and an illustrative example is analyzed.
Sales Forecasting Model Considering the Local Environment
Kim, Chul Soo ; Oh, Su Min ; Park, So Yeon ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 849~858
DOI : 10.5351/CKSS.2012.19.6.849
Today, local environmental factors has an influence on our society. Local environmental factors, as well as weather-related natural phenomena, social phenomena are also included. In this paper, numeric factors and categorical factors were analyzed, looking for a local environmental factors affecting the company's sales.Sales model by performing a regression analysis based on this was implemented.Sales model considering the local environment had an accuracy of 88.89%.
An Estimation of an Old Age Mortality Rate Using CK Model and Relational Model
Jung, Kyunam ; Kim, Donguk ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 859~868
DOI : 10.5351/CKSS.2012.19.6.859
Due to a rapidly aging society, the future Korea mortality rate is important for planning national financial strategies and social security policies. Old age mortality statistics are very limited in their ability to project a future mortality rate; therefore, it is essential to accurately estimate the old age mortality rate. In this paper, we show that the CK model with a Relational model as a base model provides accurate estimates of old age mortality rates.
The Performance of Time Series Models to Forecast Short-Term Electricity Demand
Park, W.G. ; Kim, S. ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 869~876
DOI : 10.5351/CKSS.2012.19.6.869
In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).
Maximum Tolerated Dose Estimation Applied Biased Coin Design in a Phase I Clinical Trial
Kim, Yu Rim ; Kim, Dongjae ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 877~884
DOI : 10.5351/CKSS.2012.19.6.877
Phase I trials determine the maximum tolerated dose(MTD) and the recommended dose(RD) for subsequent Phase II trials. In this paper, a MTD estimation method applied to a biased coin design is proposed for Phase I Clinical Trials. The suggested MTD estimation method is compared to the SM3 method and the NM method (Lee and Kim, 2012) using a Monte Carlo simulation study.
A Comparative Study on the Performance of Bayesian Partially Linear Models
Woo, Yoonsung ; Choi, Taeryon ; Kim, Wooseok ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 885~898
DOI : 10.5351/CKSS.2012.19.6.885
In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.
Multiple Testing in Genomic Sequences Using Hamming Distance
Kang, Moonsu ;
Communications for Statistical Applications and Methods, volume 19, issue 6, 2012, Pages 899~904
DOI : 10.5351/CKSS.2012.19.6.899
High-dimensional categorical data models with small sample sizes have not been used extensively in genomic sequences that involve count (or discrete) or purely qualitative responses. A basic task is to identify differentially expressed genes (or positions) among a number of genes. It requires an appropriate test statistics and a corresponding multiple testing procedure so that a multivariate analysis of variance should not be feasible. A family wise error rate(FWER) is not appropriate to test thousands of genes simultaneously in a multiple testing procedure. False discovery rate(FDR) is better than FWER in multiple testing problems. The data from the 2002-2003 SARS epidemic shows that a conventional FDR procedure and a proposed test statistic based on a pseudo-marginal approach with Hamming distance performs better.