• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.701-715
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• 2011

The object of study is what kinds of contents are preferable depending on regions and terminal types for high speed mobile internet. We consider 10 contents, 9 region2, and 2 terminal types. The methods are the adjusted residuals, the corresponding analysis, and the multiple corresponding analysis. The results are different, which comes from different mathematical models. 50% of results are same between the corresponding analysis and the multiple corresponding analysis. 26.3% are same between the adjusted residuals and the corresponding analysis. 21.1% are same between the adjusted residuals and the multiple corresponding analysis. We recommend the adjusted residuals because it can test hypothesis for preferring contents. The content which is not chosen by three methods is business.

• Journal of Korean Society for Quality Management
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• v.23 no.4
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• pp.58-63
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• 1995

To access the quality of a fit to a set of data it is always useful to conduct a posteriori analysis involving the examination of residuals, detection of influential data values, etc. Smoothing splines are a type of nonparametric regression estimators for the diagnostic problem. And leverage value, Cook's distance, and DFFITS are used for detecting influential data. Since high leverage points will always have small residuals, the new diagnostic measures including of properties of leverage and residuals are needed. In this paper, we propose FVARATIO version as diagnostic measure in nonparametric regression. Also we consider the rough bound as analogy with linear regression case.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.385-392
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• 2000

Many tests for multivariate normality are based on the spherical coordinates of the scaled residuals of multivariate observations. Moore and Stubblebine's (1981) Pearson chi-square test is based on the radii of the scaled residuals, or equivalently the sample Mahalanobis distances of the observations from the sample mean vector. The chi-square statistic does not have a limiting chi-square distribution since the unknown parameters are estimated from ungrouped data. We will derive a simple closed form of the Rao-Robson chi-square test statistic and provide a self-contained proof that it has a limiting chi-square distribution. We then provide an illustrative example of application to a real data with a simulation study to show the accuracy in finite sample of the limiting distribution.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.423-433
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• 2014

Test statistics using cumulative sums of residuals have been widely used in various regression models including generalized linear models(GLM). Recently, Pan and Lin (2005) extended this testing procedure to the generalized linear mixed models(GLMM) having random effects, in which we encounter difficulties in computing the marginal likelihood that is expressed as an integral of random effects distribution. The Gaussian quadrature algorithm is commonly used to approximate the marginal likelihood. Many commercial statistical packages provide an option to apply this type of goodness-of-fit test in GLMs but available programs are very rare for GLMMs. We suggest a computational algorithm to implement the testing procedure in GLMMs by a freely accessible R package, and also illustrate through practical examples.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.859-871
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• 2003

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.27-32
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• 1994

We propose a robust regression estimator which has both a high breakdown point and a bounded influence function. The main contribution of this article is to present a weight function in the generalized M (GM)-estimator. The weighting schemes which control leverage points only without considering residuals cannot be efficient, since control leverage points only without considering residuals cannot be efficient, since these schemes inevitably downweight some good leverage points. In this paper we propose a weight function which depends both on design points and residuals, so as not to downweight good leverage points. Some motivating illustrations are also given.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.429-444
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• 2005

The identification of unusual observations such as outliers and high leverage points has drawn a great deal of attention for many years. Most of these identifications techniques are based on case deletion that focuses more on the outliers than the high leverage points. But residuals together with leverage values may cause masking and swamping for which a good number of unusual observations remain undetected in the presence of multiple outliers and multiple high leverage points. In this paper we propose a new procedure to identify outliers and high leverage points simultaneously. We suggest an additive form of the residuals and the leverages that gives almost an equal focus on outliers and leverages. We analyzed several well-referred data set and discover few outliers and high leverage points that were undetected by the existing diagnostic techniques.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.361-375
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• 2015

A measure of skewness and kurtosis is proposed to test multivariate normality. It is based on an empirical standardization using the scaled residuals of the observations. First, we consider the statistics that take the skewness or the kurtosis for each coordinate of the scaled residuals. The null distributions of the statistics converge very slowly to the asymptotic distributions; therefore, we apply a transformation of the skewness or the kurtosis to univariate normality for each coordinate. Size and power are investigated through simulation; consequently, the null distributions of the statistics from the transformed ones are quite well approximated to asymptotic distributions. A simulation study also shows that the combined statistics of skewness and kurtosis have moderate sensitivity of all alternatives under study, and they might be candidates for an omnibus test.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.3
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• pp.363-369
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• 2005

This paper presents the integrated technique of water quality analysis and Geographic Information System(GIS) for assessing the variation of free chlorine residuals by water temperature and supply distance in Sangri water supply system in Daegu. GIS was utilized for mapping projectmap, extraction of a pipeline route, and supply distance. Free chlorine residual is analyzed every month for appraising the seasonal variation. As a result, free chlorine residuals are affected both water temperature and water supply distance, and it becomes worse as water temperature and water supply distance is increased. To maintain 0.4mg/l of free chlorine residual, initial dose concentration should be over 1.85mg/l in summer.

• Coupled systems mechanics
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• v.10 no.6
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• pp.545-560
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• 2021

An in situ experiment imaged via X-ray computed tomography was performed on a continuous glass fiber mat reinforced epoxy resin composite. The investigated dogbone specimen was subjected to uniaxial cyclic tension. The reconstructed scans (i.e., gray level volumes) were registered via Digital Volume Correlation. The calculated maximum principal strain fields and correlation residual maps exhibited strain localization areas within the material bulk, thus indicating damage inception and growth toward the specimen surface. Strained bands and areas of elevated correlation residuals were mainly concentrated in the narrowest gauge section of the investigated specimen, as well as on the specimen ligament edges. Gray level residuals were laid over the corresponding mesostructure to highlight and characterize damage development within the material bulk.