• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.841-849
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• 2001

The influence in fitting an equicorrelation model is investigated using the influence function. The influence functions for the model parameters are derived and its sample versions are used for investigating the influence of observations on the estimators of the parameters. Some relationships among the sample versions are found. We will derive a measure for identifying observations that have a large influence on the test of fitting the equicorrelation model using the influence function method. An example is given for illustration.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.69-74
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• 1994

Kim (1992) derived influence functions of rows and columns on the eigenvalues obtained in correspondence analysis (CA) of two-way contingency tables. As in principal component analysis, the eigenvalues are of great importance in CA. The goodness of a two dimensional correspondence plot is determined by the ratio of the sum of the two largest eigenvalues to the sum of all the eigenvalues. By investigating those rows and columns with high influence, a correspondence plot may be improved. In this paper, we extend the influence functions of CA to multiple correspondence analysis (MCA), which is a CA of multi-way contigency tables. An explicit formula of the influence function is given.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.711-722
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• 2019

Considering stress singularities at point support locations, buckling solutions for plates with arbitrary number of point supports are hard to obtain. Thus, new Hp-Cloud shape functions with Kronecker delta property (HPCK) were developed in the present paper to examine elastic buckling of point-supported thin plates in various shapes. Having the Kronecker delta property, this specific Hp-Cloud shape functions were constructed through selecting particular quantities for influence radii of nodal points as well as proposing appropriate enrichment functions. Since the given quantities for influence radii of nodal points could bring about poor quality of interpolation for plates with sharp corners, the radii were increased and the method of Lagrange multiplier was used for the purpose of applying boundary conditions. To demonstrate the capability of the new Hp-Cloud shape functions in the domain of analyzing plates in different geometry shapes, various test cases were correspondingly investigated and the obtained findings were compared with those available in the related literature. Such results concerning these new Hp-Cloud shape functions revealed a significant consistency with those reported by other researchers.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.1-26
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• 2001

In this paper, we will expand and generalize the orthogonal functions as basis functions for dynamical system representations. The orthogonal functions can be considered as generalizations of, for example, the pulse functions, Laguerre functions, and Kautz functions, and give rise to an alternative series expansion of rational transfer functions. It is shown row we can exploit these generalized basis functions to increase the speed of convergence in a series expansion. The set of Kautz functions is discussed in detail and, using the power-series equivalence, the truncation error is obtained. And so we will present the influence of noises to use Kautz function on the identification accuracy.

• Asia pacific journal of information systems
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• v.4 no.2
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• pp.131-164
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• 1994

A contingency model of outsourcing is developed from the information systems (IS) literature and strategic management literature in order to assess the following question: What factors influence change in the extent to which an organization outsources IS functions? Based on the literature, this study identifies four IS factors-gaps in information quality, IS support quality, IS staff quality, and IS cost effectiveness-and three organizational factors-the gap in financial performance, strategic orientation, and the role of information technology in an organization-that influence the change in degree of outsourcing. These factors are hypothesized to influence the change in the extent of an organization's outsourcing of IS functions. From a mail survey of 188 top IS executives in U.S. companies, the results of analysis of covariance and bivariate correlational and multivariate regression analyses provide the following major findings: (a) This study found support for the proposed research model. (b) The change in the degree of IS outsourcing is determined by gaps in information quality, IS support quality, IS cost effectiveness, and financial performance and by the role of IT among IS and organizational factors.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.623-630
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• 2003

Recently, Tanaka(1988) derived two influence functions related to an eigenvalue problem $(A-\lambda_sI)\upsilon_s=0$ of real symmetric matrix A and used them for sensitivity analysis in principal component analysis. In this paper, we deal with the perturbation expansions up to quadratic terms of the same functions and discuss the application to sensitivity analysis in principal component regression analysis(PCRA). Numerical example is given to show how the approximation improves with the quadratic term.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.453-462
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• 2005

We derive the influence function on t statistic and find its feature; the influence function on t statistic has two forms depending on the value of ${\mu}_0$. Sample influence functions are used to verify the validity of the derived influence function. We use random samples from normal distribution to show the validity of the function. The simulation study proves that the obtained influence function is very accurate to in estimating changes in t statistic when an observation is added or deleted.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.497-505
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• 2003

Under normality assumption, the tolerance interval for a future observation is sometimes of great interest in statistics. In this paper, we state the influence function on the standard deviation $\sigma$, and use it to derive the influence function on tolerance limits. Simulation study shows that the two influence functions perform very well.

• Journal of the Korean Society of Costume
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• v.51 no.7
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• pp.111-121
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• 2001

The purpose of this study was to investigate the historical changes, and analyze functions and characteristics of western men's underclothes in the second half of the 20C. This study will examine how the social backgrounds influenced on the changes of the functions of men's underclothes and how the changes of outer garments were reflected on underclothes in the second half of the 20C. In the early, the second half of the 20C, underwears of functions was continued to cleanliness and comforts. In the later of the 20C, underwears came to be seen as expressing male sexual power when it became body-conscious. By the changes of outer garments. underclothes changed the same size of proportion. In the late 1960's, the turtleneck type of shirts were copied by outer garments, and we understand that underwear can influence on outer garments. The ruffles of the 18th century reappeared in the 1960's. This reactionism of the late 20C tells us about the relation between social environments and underwear. So the social backgrounds influenced on the formativeness of men's underclothes. We understand that underwear can influence on outer garments and outer garments can influence on underwear, too. The important characteristics of the second half of the 20C were the remarkable resemblance of some styles to those of the Past and the occasional blurring of the distinction between underwear and outerwear.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.4
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• pp.532-539
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• 2007

The purpose of this study was to investigate the influence of cooking wine's functions on food quality attributes. factor analysis, reliability analysis (Cronbach's $\alpha$), and multiple regression analysis were employed to analyze the data. The cooking wine functions were divided into 3 factors (expectation of utility, functionality, and quality enhancement). According to the multiple regression analysis of cooking wine factors to food quality, all factors had positive influences on food quality. Among the three factors, expectation of utility(=.556, p<0.001) had the most significant influence on food quality. And functionality (=.321, p<0.001) and quality enhancement(=.296, p<=0.001) also had significant effects in that order. further research should be conducted on cooking wine's utility aspects and their effects on food quality. Finally, we anticipate that the results of this study will be useful information for food-service companies.