• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.2
• /
• pp.357-364
• /
• 1996

This paper presents a new blind identification method of nonminimum phase FIR systems without employing higher-order statistics. It is based on the observation that the absolute mean of a second-order white sequence can measure the higher-order whiteness of the sequence. The proposed method may be a new alternative way to the higher-order statistics approaches. Some computer simulations show that the absolute mean is exactly estimated and the proposed method can overcome the disadvantages of the higher-order statistics approaches.

• Communications for Statistical Applications and Methods
• /
• v.21 no.1
• /
• pp.81-91
• /
• 2014

This study derives the characteristic functions of (multivariate/generalized) t distributions without contour integration. We extended Hursts method (1995) to (multivariate/generalized) t distributions based on the principle of randomization and mixtures. The derivation methods are relatively straightforward and are appropriate for graduate level statistics theory courses.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.10
• /
• pp.6019-6023
• /
• 2013

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

• Communications for Statistical Applications and Methods
• /
• v.16 no.4
• /
• pp.647-658
• /
• 2009

It is already known from the previous study that flood seems to have heavier tail. Therefore, to make prediction of future extreme label, some agreement of tail behavior of extreme data is highly required. The LH-moments estimation method, the generalized form of L-moments is an useful method of characterizing the upper part of the distribution. LH-moments are based on linear combination of higher order statistics. In this study, we have formulated LH-moments of five distributions useful in hydrology such as, two types of three parameter kappa distributions, beta-${\kappa}$ distribution, beta-p distribution and a generalized Gumbel distribution. Using LH-moments reduces the undue influences that small sample may have on the estimation of large return period events.

• The Korean Journal of Applied Statistics
• /
• v.24 no.6
• /
• pp.1077-1094
• /
• 2011

We accomplish clustering analyses for yeast cell cycle microarray expression data. To reflect the characteristics of a time-course data, we screen the genes using the test statistics with Fourier coefficients applying a FDR procedure. We compare the results done by model-based clustering, K-means, PAM, SOM, hierarchical Ward method and Fuzzy method with the yeast data. As the validity measure for clustering results, connectivity, Dunn index and silhouette values are computed and compared. A biological interpretation with GO analysis is also included.

• The Korean Journal of Applied Statistics
• /
• v.24 no.1
• /
• pp.127-136
• /
• 2011

Multiplicative noise model is the one of popular method for masking continuous variables. In this paper, we propose the transformation on the variable to which random noise was multiplied. An advantage of the masking method using proposed transformation is that the masking data users can obtain the unbiased values of mean and variance of original (unmasked) data. We also consider the data utility and correlation structure of variables when we apply the proposed multiplicative noise scheme. To investigate the properties of the method of masking based on multiplicative noise, a simulation study has been conducted using the 2008 Householder Income and Expenditure Survey data.

• The Korean Journal of Applied Statistics
• /
• v.20 no.2
• /
• pp.229-244
• /
• 2007

Among the small area estimation methods, it has been known that hierarchical Bayesian(HB) approach is the most reasonable and effective method. However any model based approaches need good explanatory variables and finding them is the key role in the model based approach. As the lacking of explanatory variables, adopting the spatial terms in the model was introduced. Here in this paper, we evaluate the model based methods with/without spatial terms using the diagnostic methods which were introduced by Brown et al. (2001). And Economic Active Population Survey(2005) is used for data analysis.

• Communications for Statistical Applications and Methods
• /
• v.23 no.2
• /
• pp.119-129
• /
• 2016

A new sampling method is introduced based on the idea of a ranked set sampling scheme in which taken samples in each set are dependent on previous ones. Some theoretical results are presented and distribution-free confidence intervals are derived for the quantiles of any continuous population. It is shown numerically that the proposed sampling scheme may lead to 95% confidence intervals (especially for extreme quantiles) that cannot be found based on the ordinary ranked set sampling scheme presented by Chen (2000) and Balakrishnan and Li (2006). Optimality aspects of this scheme are investigated for both coverage probability and minimum expected length criteria. A real data set is also used to illustrate the proposed procedure. Conclusions are eventually stated.

• Communications for Statistical Applications and Methods
• /
• v.20 no.5
• /
• pp.405-416
• /
• 2013

This paper develops a maximum profile likelihood estimator of unknown parameters of the exponentiated Gumbel distribution based on upper record values. We propose an approximate maximum profile likelihood estimator for a scale parameter. In addition, we derive Bayes estimators of unknown parameters of the exponentiated Gumbel distribution using Lindley's approximation under symmetric and asymmetric loss functions. We assess the validity of the proposed method by using real data and compare these estimators based on estimated risk through a Monte Carlo simulation.

• The Korean Journal of Applied Statistics
• /
• v.29 no.7
• /
• pp.1271-1281
• /
• 2016

Wins above replacement (WAR) is one of the most widely used statistic among sabermatrics statistics that measure the ability of a batter in baseball. WAR has a great advantage that is to represent the attack power of the player and the base running ability, defensive ability as a single value. In this study, we proposed a hitter ability index using the sabermetrics statistics that can replace WAR based on Korea Baseball Record Data of the last three years (2013-2015). First, we calculated Batter ability index through the arithmetic mean method, the weighted average method, principal component regression and selected the method that had high correlation with WAR.