• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.151-165
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• 2006

It is important to estimate the true misclassification rate of a given classifier when an independent set of test data is not available. Cross-validation and bootstrap are two possible approaches in this case. In related literature bootstrap estimators of the true misclassification rate were asserted to have better performance for small samples than cross-validation estimators. We compare the two estimators empirically when the classification rule is so adaptive to training data that its apparent misclassification rate is close to zero. We confirm that bootstrap estimators have better performance for small samples because of small variance, and we have found a new fact that their bias tends to be significant even for moderate to large samples, in which case cross-validation estimators have better performance with less computation.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.781-791
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• 2012

A $2{\times}2$ 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 $2{\times}2$ 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.

• Membrane and Water Treatment
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• v.10 no.4
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• pp.251-257
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• 2019

Fabricating hydrophobic porous membrane is important for exploring the applications of membrane distillation (MD). In the present paper, poly(vinylidene fluoride) (PVDF) hollow fiber membrane was modified by coating polydimethylsiloxane (PDMS) on its surface. The effects of PDMS concentration, cross-linking temperature and cross-linking time on the performance of the composite membranes in a vacuum membrane distillation (VMD) process were investigated. It was found that the hydrophobicity and the VMD performance of the PVDF hollow fiber membrane were obviously improved by coating PDMS. The optimal PDMS concentration, cross-linking temperature and cross-linking time were 0.5 wt%, $80^{\circ}C$, and 9 hr, respectively.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.655-664
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• 2022

On the motivation by an integrative study of multi-omics data, we are interested in estimating the structure of the sparse cross correlation matrix of two high-dimensional random vectors. We rewrite the problem as a multiple testing problem and propose a new method to estimate the sparse structure of the cross correlation matrix. To do so, we test the correlation coefficients simultaneously and threshold the correlation coefficients by controlling FRD at a predetermined level α. Further, we apply the proposed method and an alternative adaptive thresholding procedure by Cai and Liu (2016) to the integrative analysis of the protein expression data (X) and the mRNA expression data (Y) in TCGA breast cancer cohort. By varying the FDR level α, we show that the new procedure is consistently more efficient in estimating the sparse structure of cross correlation matrix than the alternative one.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.205-211
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• 2008

This paper deals with the estimations of kernel ridge regression when the responses are subject to randomly right censoring. The iterative reweighted least squares(IRWLS) procedure is employed to treat censored observations. The hyperparameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation(GCV) function. Experimental results are then presented which indicate the performance of the proposed procedure.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.105-114
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• 2014

In this paper we suggest an efficient method to estimate the distribution function using the Bezier curve, and compare it with existing methods by simulation studies. In addition, we suggest a robust version of cross-validation criterion to estimate the number of Bezier points, and showed that the proposed method is better than the existing methods based on simulation studies.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.743-758
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• 2005

This paper consider penalized likelihood regression with data from exponential family. The fast computation method applied to Gaussian data(Kim and Gu, 2004) is extended to non Gaussian data through asymptotically efficient low dimensional approximations and corresponding algorithm is proposed. Also smoothing parameter selection is explored for various exponential families, which extends the existing cross validation method of Xiang and Wahba evaluated only with Bernoulli data.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.151-158
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• 1999

Distribution-free tests are proposed for AB/BA 2*2 cross-over design data based on placements introduced by Orban and Wolfe(1992). In this paper we suggest the homogeneity test or carry-over effects and also suggest the test for direct effects and the test for period effects under the same carry-over effects. The properties such as iterative asymptotic distribution for the proposed tests are discussed.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.146-154
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• 1995

By using simple Taylor expansion, we derive an easy bias-correction rule for the apparent prodiction error of the predictor defined by the general M-estimators with respect to an arbitrary measure of prediction error. Our method has a considerable computational advantage over the previous methods based on the resampling thchnique such as Cross-validaton and Boothtrap. Connections with AIC, Cross-Validation and Boothtrap are discussed too.

• International Journal of Reliability and Applications
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• v.3 no.3
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• pp.125-132
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• 2002

Sometimes we have two groups of inbred lines and there are only interest in gca comparisons within two groups of lines of sizes$\P_1$ and $\P_@$, not between two groups. For example, suppose there two Lab, each of the 2 Labs have obtained the best line. For this purpose we now give a method of constructing block designs for diallel cross experiments and we will explain how to calculate efficiency. Then we show the efficiencies in the table.