• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.489-501
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• 1999

In this paper, we consider the panel data regression model in which the disturbances have nested error component. We derive a Lagrange Multiplier(LM) test which is jointly testing for the presence of random individual effects and nested effects under the normality assumption of the disturbances. This test extends the earlier work of Breusch and Pagan(1980) and Baltagi and Li(1991). Further, it is shown that this LM test has the same asymptotic distribution without normality assumption of the disturbances.

• Journal of the Korean Statistical Society
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• v.18 no.1
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• pp.46-61
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• 1989

This paper is concerned with the development of a nonparametric procedure for the statistical inference about the nonlinear regression parameters. A confidence region and a hypothesis testing procedure based on a class of signed linear rank statistics are proposed and the asymptotic distributions of the test statistic both under the null hypothesis and under a sequence of local alternatives are investigated. Some desirable asymptotic properties including the asymptotic relative efficiency are discussed for various score functions.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.565-579
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• 1997

A robust test is proposed for the problem of testing the parallelism of several regression lines against ordered alternatives. The proposed test statistic is based on a linear combination of one-step pairwise GM-estimators. We compare the performance of the proposed test with that of the other tests through a Monte Carlo simulation. The results of the simulation study show that the proposed test has stable levels, good empirical powers in various circumstances, and particularly higher empirical powers under the presence of extreme outliers or leverage points.

• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.107-109
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• 1979

Consider a linear model with n observations and k explanatory variables: (1)b $y=X\beta+u, u\simN(0,\sigma^2I_n)$. We assume that the model satisfies the ideal conditions. Consider the general linear constraints on regression coefficient vector: (2) $R\beta=r$, where R and r are known matrices of orders $q\timesk$ and q\times1$ respectively, and the rank of R is $qk+q$.

• The Korean Journal of Applied Statistics
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• v.5 no.1
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• pp.29-39
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• 1992

A testing and estimation procedure is considered for changes at unknown time point in simple linear regression model. A test statistic of quadratic form is suggested. We also discuss the asymptotic distribution and its level control. The proposed method is compared with the likelihood ratio test through a example.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.655-665
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• 2000

Several information criterions, Schwarz information criterion (SIC), Akaike information criterion (AIC), and the modified Akaike information criterion ($AIC_c$), are proposed to locate a change point in the multiple linear regression model. These methods are applied to a stock Exchange data set and compared to the results.

• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.17-26
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• 1978

For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1152-1158
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• 2007

Although various fast and simple, testing devices have been developed in many countries such as the U.S, Japan, and European countries, these testing devices are not commonly used in Korea. In this study, compaction fur the field density test was carried out with a hand-guided vibrating roller. The results of the field density test were compared with those of the new testing devices such as the geogauge, soil impact hammer(CASPFOL), light falling weight deflectometer(LFWD), dynamic cone penetration(DCP). Regression analyses were conducted with the data from new testing devices. The analysis results showed that the correlation coefficients were high in the range of $70{\sim}95%$.

• Journal of Korean Neurosurgical Society
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• v.64 no.2
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• pp.309-315
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• 2021

Objective : To explore the correlation between the polymorphism of histone deacetylase 9 gene (rs1060499865, rs723296, rs957960) and ischemic stroke (IS) in Chinese Han population in Dali region. Methods : This study included 155 IS patients and 128 healthy physical examinees. TaqMan-polymerase chain reaction technology and multivariate logistic regression were performed. Results : In the case group, there was no polymorphism of rs1060499865 observed in the two groups; whereas on the rs723296 locus the frequencies of C allele and TC genotype were significantly higher than that in the control group, alleles C and T were associated with a 2.158-fold increase in IS risk, and genotypes TC and TT were associated with a 2.269-fold increase in IS risk. The locus rs957960 exhibited no significant difference between the two groups. Conclusion : An association between rs723296 and the risk of IS was found in the Chinese Han population in Dali region. No significant association was found between rs1060499865, rs957960 and IS in the Chinese Han population in Dali region.