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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
The Biometry-Mendelian Controversy in the History of Statistics
Jo, Jae-Keun ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 303~324
DOI : 10.5351/CKSS.2008.15.3.303
From mid-1890's, biometricians and Mendelians debated over Darwin's evolutionary theory. Biologist W. Weldon and Mathematician K. Pearson were leaders of the biometric school and biologist W. Bateson led Mendelian school. In this paper topics of the controversy such as causation vs. correlation, frequency distribution are considered. And in relation to the tradition of British statistics, we consider the philosophy of Karl Pearson revealed in this debate. Besides many statistical methods and concepts by Karl Pearson, the newly born mathematical statistics got a new journal Biometrika, a department in university, and a school of researchers from this controversy.
Reliability in Two Independent Uniform and Power Function-Half Normal Distribution
Woo, Jung-Soo ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 325~332
DOI : 10.5351/CKSS.2008.15.3.325
We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.
Variable Selection Theorem for the Analysis of Covariance Model
Yoon, Sang-Hoo ; Park, Jeong-Soo ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 333~342
DOI : 10.5351/CKSS.2008.15.3.333
Variable selection theorem in the linear regression model is extended to the analysis of covariance model. When some of regression variables are omitted from the model, it reduces the variance of the estimators but introduces bias. Thus an appropriate balance between a biased model and one with large variances is recommended.
Simple Graphs for Complex Prediction Functions
Huh, Myung-Hoe ; Lee, Yong-Goo ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 343~351
DOI : 10.5351/CKSS.2008.15.3.343
By supervised learning with p predictors, we frequently obtain a prediction function of the form
, it is not easy to understand the inner structure of f, except for the case the function is formulated as additive. In this study, we propose to use p simple graphs for visual understanding of complex prediction functions produced by several supervised learning engines such as LOESS, neural networks, support vector machines and random forests.
Sample Size Calculations with Dropouts in Clinical Trials
Lee, Ki-Hoon ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 353~365
DOI : 10.5351/CKSS.2008.15.3.353
The sample size in a clinical trial is determined by the hypothesis, the variance of observations, the effect size, the power and the significance level. Dropouts in clinical trials are inevitable, so we need to consider dropouts on the determination of sample size. It is common that some proportion corresponding to the expected dropout rate would be added to the sample size calculated from a mathematical equation. This paper proposes new equations for calculating sample size dealing with dropouts. Since we observe data longitudinally in most clinical trials, we can use a last observation to impute for missing one in the intention to treat (ITT) trials, and this technique is called last observation carried forward(LOCF). But LOCF might make deviations on the assumed variance and effect size, so that we could not guarantee the power of test with the sample size obtained from the existing equation. This study suggests the formulas for sample size involving information about dropouts and shows the properties of the proposed method in testing equality of means.
Estimation for the Double Rayleigh Distribution Based on Multiply Type-II Censored Samples
Han, Jun-Tae ; Kang, Suk-Bok ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 367~378
DOI : 10.5351/CKSS.2008.15.3.367
In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the location parameter in a double Rayleigh distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.
The Choice of a Primary Resolution and Basis Functions in Wavelet Series for Random or Irregular Design Points Using Bayesian Methods
Park, Chun-Gun ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 379~386
DOI : 10.5351/CKSS.2008.15.3.379
In this paper, the choice of a primary resolution and wavelet basis functions are introduced under random or irregular design points of which the sample size is free of a power of two. Most wavelet methods have used the number of the points as the primary resolution. However, it turns out that a proper primary resolution is much affected by the shape of an unknown function. The proposed methods are illustrated by some simulations.
Optimal Two-Stage Periodic Inspection Policy for Maintaining Storage Reliability
Cho, Yong-Suk ; Lee, Joo-Ho ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 387~402
DOI : 10.5351/CKSS.2008.15.3.387
In this thesis we propose a two-stage periodic inspection model for maintaining the reliability of a system in long-term storage. There are two types of tests available; a fallible test and an error-free test. The system is overhauled at detection of failure or when the storage reliability after inspection becomes less than or equal to the prespecified value. The expected cost per unit time until overhaul is derived and a procedure for minimizing the expected cost is suggested. The two-stage periodic inspection model is compared with the one-stage periodic inspection model for various parameters of the cost function when the failure time follows exponential and Weibull distributions. The proposed model is then applied to an existing missile system for comparison with the current inspection policy.
The Size of the Cochran-Armitage Trend Test in 2 X C Contingency Tables: Two Multinomial Distribution Case
Kang, Seung-Ho ; Ahn, Sun-Young ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 403~409
DOI : 10.5351/CKSS.2008.15.3.403
In this paper we show that the peak of the type I error rate of the Oochran-Armitage trend test could be greater than the nominal level when
contingency tables obtained from two multinomial distributions are extremely unbalanced. This result justifies the use of the exact Cochran-Armitage trend test in extremely unbalanced
A Feasible Two-Step Estimator for Seasonal Cointegration
Seong, Byeong-Chan ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 411~420
DOI : 10.5351/CKSS.2008.15.3.411
This paper considers a feasible two-step estimator for seasonal cointegration as the extension of
(2005). It is shown that the reducedrank maximum likelihood(ML) estimator for seasonal cointegration can still produce occasional outliers as that for non-seasonal cointegration even though the sizes of them are not extreme as those in non-seasonal cointegration. The ML estimator(MLE) is compared with the two-step estimator in a small Monte Carlo simulation study and we find that the two-step estimator can be an attractive alternative to the MLE, especially, in a small sample.
Test and Estimation for Exponential Mean Change
Kim, Jae-Hee ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 421~427
DOI : 10.5351/CKSS.2008.15.3.421
This paper deals with the problem of testing for the existence of change in mean and estimating the change-point when the data are from the exponential distributions. The likelihood ratio test statistic and Gombay and Horvath (1990) test statistic are compared in a power study when there exists one change-point in the exponential means. Also the change-point estimator using the likelihood ratio and the change-point estimators based on Gombay and Horvath (1990) statistic are compared for their detecting capability via simulation.
Noninformative Priors for the Coefficient of Variation in Two Inverse Gaussian Distributions
Kang, Sang-Gil ; Kim, Dal-Ho ; Lee, Woo-Dong ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 429~440
DOI : 10.5351/CKSS.2008.15.3.429
In this paper, we develop the noninformative priors when the parameter of interest is the common coefficient of variation in two inverse Gaussian distributions. We want to develop the first and second order probability matching priors. But we prove that the second order probability matching prior does not exist. It turns out that the one-at-a-time and two group reference priors satisfy the first order matching criterion but Jeffreys' prior does not. The Bayesian credible intervals based on the one-at-a-time reference prior meet the frequentist target coverage probabilities much better than that of Jeffreys' prior. Some simulations are given.
Multiclass Classification via Least Squares Support Vector Machine Regression
Shim, Joo-Yong ; Bae, Jong-Sig ; Hwang, Chang-Ha ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 441~450
DOI : 10.5351/CKSS.2008.15.3.441
In this paper we propose a new method for solving multiclass problem with least squares support vector machine(LS-SVM) regression. This method implements one-against-all scheme which is as accurate as any other approach. We also propose cross validation(CV) method to select effectively the optimal values of hyper-parameters which affect the performance of the proposed multiclass method. Experimental results are then presented which indicate the performance of the proposed multiclass method.
Statistical Inference for Process Capability Indices and 6 Sigma Qualify Levels
Cho, Joong-Jae ; Sim, Kyu-Young ; Park, Byoung-Sun ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 451~464
DOI : 10.5351/CKSS.2008.15.3.451
Six sigma is the rating that signifies "best in clas", with only 3.4 defects per million units or operations. Higher sigma quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The process capability indices and the sigma level
have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider statistical inference for process capability indices
. Also, we study better testing procedure on assessing sigma level
and capability index
, for practitioners to use in determining whether a given process is capable. The proposed method is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.
Development of Estimation Algorithm of Latent Ability and Item Parameters in IRT
Choi, Hang-Seok ; Cha, Kyung-Joon ; Kim, Sung-Hoon ; Park, Chung ; Park, Young-Sun ;
Communications for Statistical Applications and Methods, volume 15, issue 3, 2008, Pages 465~481
DOI : 10.5351/CKSS.2008.15.3.465
Item response theory(IRT) estimates latent ability of a subject based on the property of item and item parameters using item characteristics curve(ICC) of each item case. The initial value and another problems occurs when we try to estimate item parameters of IRT(e.g. the maximum likelihood estimate). Thus, we propose the asymptotic approximation method(AAM) to solve the above mentioned problems. We notice that the proposed method can be thought as an alternative to estimate item parameters when we have small size of data or need to estimate items with local fluctuations. We developed 'Any Assess' and tested reliability of the system result by simulating a practical use possibility.