• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.557-587
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• 2005

This paper elucidates the limiting Gaussian distribution of a class of rank order statistics {$T_N$} for two sample problem pertaining to empirical processes of the squared residuals from two independent samples of GARCH processes. A distinctive feature is that, unlike the residuals of ARMA processes, the asymptotics of {$T_N$} depend on those of GARCH volatility estimators. Based on the asymptotics of {$T_N$}, we empirically assess the relative asymptotic efficiency and effect of the GARCH specification for some GARCH residual distributions. In contrast with the independent, identically distributed or ARMA settings, these studies illuminate some interesting features of GARCH residuals.

• Journal of the Korean Statistical Society
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• v.21 no.1
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• pp.59-69
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• 1992

A measure is proposed to represent the degree of residuals from the symmetry model for square contingency tables with nominal categories. The measure is derivedby modifying the sum of squared singular values for a skew symmetric matrix of the residuals from the symmetry model. The proposed measure would be useful for comparing the degree of residuals from the symmetry model in several tables.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.259-269
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• 2017

Due to the nonnegativity of variance, most of nonparametric estimations of discontinuous variance function have used the Nadaraya-Watson estimation with residuals. By the modification of Chen et al. (2009) and Yu and Jones (2004), Huh (2014, 2016a) proposed the estimators of the log-variance function instead of the variance function using the local linear estimator which has no boundary effect. Huh (2016b) estimated the variance function using the adjusted squared residuals by the estimated jump size in the discontinuous variance function. In this paper, we propose an estimator of the discontinuous log-variance function using the local linear estimator with the adjusted log-squared residuals by the estimated jump size of log-variance function like Huh (2016b). The numerical work demonstrates the performance of the proposed method with simulated and real examples.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.115-122
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• 2006

A test is suggested for detecting deviations from both multivariate normality and independence. This test can be used for assessing the normality and independence of univariate time series residuals. We derive the limiting distribution of the test statistic and a simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we apply our method to a real data of time series.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.411-416
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• 1998

A simple nonparametric test of complete or total independence is suggested for continuous multivariate distributions. This procedure first discretizes the original variables based on their order statistics, and then tests the hypothesis of complete independence for the resulting contingency table. Under the hypothesis of independence, the chi-squared test statistic has an asymptotic chi-squared distribution. We present a simulation study to illustrate the accuracy in finite samples of the limiting distribution of the test statistic. We compare our method to another nonparametric test of complete independence via a simulation study. Finally, we apply our method to the residuals from a real data set.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.59-74
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• 1996

The properties of the residuals are investigated when K-consecutive observations are interpolated. The central limit theorem is also proved for the LSE for autoregressive parameters when $\kappa4--consecutive observations are contaminated. The performance of the interpolated LSE in small samples is investigated by simulation. And the interpolated with the Yule-Walker type estimator.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.87-95
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• 2014

In the regression model, Kang and Huh (2006) studied the estimation of the discontinuous variance function using the Nadaraya-Watson estimator with the squared residuals. The local linear estimator of the log-variance function, which may have the whole real number, was proposed by Huh (2013) based on the kernel weighted local-likelihood of the ${\chi}^2$-distribution. Chen et al. (2009) estimated the continuous variance function using the local linear fit with the log-squared residuals. In this paper, the estimator of the discontinuous log-variance function itself or its derivative using Chen et al. (2009)'s estimator. Numerical works investigate the performances of the estimators with simulated examples.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.2019-2031
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• 2004

The least-squares formulation for rigid-plasticity based on J$_2$-flow rule and infinitesimal theory and its meshfree implementation using moving least-squares approximation are proposed. In the least-squares formulation the squared residuals of the constitutive and equilibrium equations are minimized. Those residuals are represented in a form of first-order differential system using the velocity and stress components as independent variables. For the enforcement of the boundary and frictional contact conditions, penalty scheme is employed. Also the reshaping of nodal supports is introduced to avoid the difficulties due to the severe local deformation near the contact interface. The proposed least-squares meshfree method does not require any structure of extrinsic cells during the whole process of analysis. Through some numerical examples of metal forming processes, the validity and effectiveness of the method are investigated.

• Journal of the Korean Statistical Society
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• v.34 no.2
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• pp.161-172
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• 2005

In this paper a nonparametric method is proposed for detecting conditionally heteroscedastic errors in a nonparametric time series regression model where the observation points are equally spaced on [0,1]. It turns out that the first-order sample autocorrelation of the squared residuals from the kernel regression estimates provides essential information. Illustrative simulation study is presented for diverse errors such as ARCH(1), GARCH(1,1) and threshold-ARCH(1) models.

• Journal of Korean Critical Care Nursing
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• v.12 no.3
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• pp.74-83
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• 2019

Purpose : The routine evaluation of gastric residuals (RGR) is considered standard care for premature infants. This study evaluated the usefulness of RGR in premature infants. Methods : The study retrospectively investigated 208 premature infants (gestational aged under 34 weeks) who underwent gavage feeding in a neonatal intensive care unit at a tertiary hospital. The patients were divided into two groups: RGR (n=104) and no-RGR (n=104). Those in the no-RGR group had their gastric residuals checked only if signs of feeding intolerance were present. Clinical outcomes, including the time to reach full enteral feeding (FEF) and the incidences of gastrointestinal disorders such as feeding intolerance (FI) and necrotizing enterocolitis (NEC), were compared. Data were analyzed with SPSS ver. 21, using a Mann-Whitney U test, chi-squared test, and Fisher's exact test. Results : There was no statistically significant difference for the time to FEF (z=-0.61, p=.541), incidence of FI ($X^2=0.38$, p=.540), and NEC ($X^2=1.42$, p=.234) between the two groups. Conclusion : No-RGR did not increase the risk for FI or NEC. These results suggest that RGR evaluation may not improve nutritional outcomes in premature infants. Recommendations for further research and practice guidelines will be provided.