• 대한기계학회논문집A
• /
• 제28권12호
• /
• pp.2019-2031
• /
• 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 Data and Information Science Society
• /
• 제27권2호
• /
• pp.559-564
• /
• 2016

The Durbin-Watson (DW) test in regression model and the Ljung-Box (LB) test in ARMA (autoregressive moving average) model are typical examples of correlated error tests. The DW test is used for detecting autocorrelation of errors using the residuals from a regression analysis. The LB test is used for specifying the correct ARMA model using the first some sample autocorrelations based on the residuals of a tted ARMA model. In this article, simulations with four data generating processes have been carried out to evaluate their performances as correlated error tests. Our simulations show that the DW test is severely dependent on the assumed AR(1) model but isn't sensitive enough to reject the misspecified model and that the LB test reports lackluster performance in general.

• Journal of the Korean Data and Information Science Society
• /
• 제28권5호
• /
• pp.1191-1204
• /
• 2017

Weighted least squares (WLS) estimation is often easily used for the data with heteroscedastic errors because it is intuitive and computationally inexpensive. However, WLS estimator is less robust to a few outliers and sometimes it may be inefficient. In order to overcome robustness problems, Box-Cox transformation, Huber's M estimation, bisquare estimation, and Yohai's MM estimation have been proposed. Also, more efficient estimations than WLS have been suggested such as Bayesian methods (Cepeda and Achcar, 2009) and semiparametric methods (Kim and Ma, 2012) in heteroscedastic error models. Recently, Çelik (2015) proposed the weight methods applicable to the heteroscedasticity patterns including butterfly-distributed residuals and megaphone-shaped residuals. In this paper, we review heteroscedastic regression estimators related to robust or efficient estimation and describe their properties. Also, we analyze cost data of U.S. Electricity Producers in 1955 using the methods discussed in the paper.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2005년도 춘계학술대회 논문집
• /
• pp.1463-1467
• /
• 2005

This paper proposes an analytical redundancy technique for fault diagnostics of the sensor in steer-by-wire system. We use incorporating vehicle dynamics modeling into the design of a diagnostic system for steer-by-wire system. The use of a model of vehicle dynamics improves the speed and accuracy of the diagnoses. The proposed fault diagnostics algorithm is based on parity-space methods to generate residuals. To reduce the effects of modeling uncertainty and dynamic transients, the residuals are subject to filtering. We construct diagnostic system consisting residual threshold for detection and isolator with using the directional residual vector.

• 한국군사과학기술학회지
• /
• 제14권5호
• /
• pp.957-964
• /
• 2011

New time schemes based on the FEM were developed and their performances were tested with 2D wave equation. The least-squares and weighted residual methods are used to construct new time schemes based on traditional residual minimization method. To overcome some drawbacks that time schemes based on the least-squares and weighted residual methods have, ad-hoc method is considered to minimize residuals multiplied by others residuals as a new approach. And variational method is used to get necessary conditions of ad-hoc minimization. A-stability was chosen to check the stability of newly developed time schemes. Specific values of new time schemes are presented along with their numerical solutions which were compared with analytic solution.

• Communications for Statistical Applications and Methods
• /
• 제13권3호
• /
• pp.635-649
• /
• 2006

In this paper, we perform a simulation study of genetic model-free age-of-onset methods in linkage tests which has been proposed by Zhu et al. (1997). They performe. Haseman-Elston regression on a set of bipolar pedigree data using each of three dependent variables: a binary trait indicating disease concordance or discordance, a binary trait adjusted for age-of-onset, and the residuals from a survival analysis. We compare the powers of the proposed test statistics for various situations. Simulations that we have carried out show that the gains in power are observed when the residuals from a survival analysis are used in linkage tests.

• Communications for Statistical Applications and Methods
• /
• 제10권3호
• /
• pp.873-878
• /
• 2003

LS-SVM(Least-Squares Support Vector Machine) has been used as a promising method for regression as well as classification. Suykens et al.(2000) used only the magnitude of residuals to obtain SVs(Support Vectors). Suykens' method behaves well for homogeneous model. But in a heteroscedastic model, the method shows a poor behavior. The present paper proposes a new method to get SVs. The proposed method uses the variance of noise as well as the magnitude of residuals to obtain support vectors. Through the simulation study we justified excellence of our proposed method.

• 품질경영학회지
• /
• 제24권3호
• /
• pp.50-64
• /
• 1996

This article is concerned with procedures for detecting multiple y outliers in linear regression. The outward-testing procedure, which is controled by the initial subset and the minimum residuals, is suggested by two phases. The performance of this procedure is compared with others by Monte Carlo techniques and found to be superior. The procedure, however, fails in detecting y outliers that are on high-leverage cases in Phase 1. Thus, we proposed ELMS algorithm for a set of suspect observations, in Phase 1. In Phase 2, the proposed testing is conducted using the studentized residuals to see which of the suspect cases are outliers. Several examples are analyzed.

• Communications for Statistical Applications and Methods
• /
• 제16권4호
• /
• pp.587-594
• /
• 2009

이 논문에서는 선형회귀모형의 오차항에 대한 변화점 검정 문제를 다룬다. 고정 혹은 변동 모형의 독립 변수와 약한 종속성을 가지는 오차항을 가정하는 관계로 통상적인 중회귀모형뿐만 아니라 ARMA 등의 시계열 모형까지 본 논문에서 포괄한다고 하겠다. 오차항의 분포 변화를 검정하기 위하여 회귀모형의 잔차에 기초한 확률밀도함수 추정값을 이용한다. 적절한 가정하에서 잔차를 이용한 검정이 실제 오차를 이용한 경우와 동일한 극한 분포를 가짐을 보였다.

• Communications for Statistical Applications and Methods
• /
• 제13권1호
• /
• pp.177-190
• /
• 2006

The aim of this study is to propose a Bayesian model for fitting mortality rate of colon cancer. For the analysis of mortality rate of a disease, factors such as age classes of population and spatial characteristics of the location are very important. The model proposed in this study allows the age class to be a random effect in addition to its conventional role as the covariate of a linear regression, while the spatial factor being a random effect. The model is fitted using Metropolis-Hastings algorithm. Posterior expected predictive deviances, standardized residuals, and residual plots are used for comparison of models. It is found that the proposed model has smaller residuals and better predictive accuracy. Lastly, we described patterns in disease maps for colon cancer.