• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.463-471
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• 2019

The variable transformations are useful ways to guarantee the functional relationships in the model. However, the presence of outliers may undermine the accuracy of transformation. This paper deals with response transformations in the partial linear models under the existence of outliers. A new procedure for response transformation and outliers detection is proposed. The procedure uses a sequential method for identifying outliers and dynamic graphical methods for an appropriate transformation. The graphical tools make it possible to catch diagnostic information by monitoring the movement of points in the data. The procedure is illustrated with several examples. Examples show that visual clues regarding the optimal transformation, the fittness of the model and the outlyness of the observations can be checked from the series of plots.

• Proceedings of the Zoological Society Korea Conference
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• 1996.10a
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• pp.248.1-248
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• 1996

No Abstract, See Full Text

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.245-256
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• 2014

This work is focused on the boundary layer and heat transfer characteristics of hydromagnetic flow over a stretching sheet with variable thickness. Steady, two dimensional, nonlinear, laminar flow of an incompressible, viscous and electrically conducting fluid over a stretching sheet with variable thickness and power law velocity in the presence of variable magnetic field and variable temperature is considered. Governing equations of the problem are converted into ordinary differential equations utilizing similarity transformations. The resulting non-linear differential equations are solved numerically by utilizing Nachtsheim-Swigert shooting iterative scheme for satisfaction of asymptotic boundary conditions along with fourth order Runge-Kutta integration method. Numerical computations are carried out for various values of the physical parameters and the effects over the velocity and temperature are analyzed. Numerical values of dimensionless skin friction coefficient and non-dimensional rate of heat transfer are also obtained.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.205-213
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• 2012

Transforming response variable is a general tool to adapt data to a linear regression model. However, it is well known that response transformations in linear regression are very sensitive to one or a few outliers. Many methods have been suggested to develop transformations that will not be influenced by potential outliers. Recently Cheng (2005) suggested to using a trimmed likelihood estimator based on the idea of the least trimmed squares estimator(LTS). However, the method requires presetting the number of outliers and needs many computations. A new method is proposed, that can solve the problems addressed and improve the robustness of the estimates. The method uses a stepwise procedure, suggested by Hadi and Simonoff (1993), to detect outliers that determine response transformations.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.163-178
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• 2023

GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.713-720
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• 2018

In this paper a new numerical method to determine the elastic curve of the simply supported beams of variable cross-section is demonstrated. In general case it needs to solve linear or small nonlinear second order differential equations with prescribed boundary conditions. For numerical solution the initial values of the slope and the deflection of the end cross-section of the beam is necessary. For obtaining the initial values a lively procedure is developed: it is a special application of the shooting method because boundary value problems can be transformed into initial value problems. As a result of these transformations the initial values of the differential equations are obtained with high accuracy. Procedure is applied for calculating of elastic curve of a simply supported beam of variable cross-section. Results of these numerical procedures, analytical solution of the linearized version and finite element method are compared. It is proved that the suggested procedure yields technically accurate results.

• International Journal of Contents
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• v.1 no.1
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• pp.40-44
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• 2005

This paper introduces region partitioning method of non-perfect nested loops with non-uniform dependences. This kind of loop normally can't be parallelized by existing parallelizing compilers and transformations. Even when parallelized in rare instances, the performance is very poor. Based on the Convex Hull theory which has adequate information to handle non-uniform dependences, this paper proposes an enhanced region partitioning method which divides the iteration space into minimum parallel regions where all the iterations inside each parallel region can be executed in parallel by using variable renaming after copying.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.563-571
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• 2001

In this paper, we study selecting a transformation so that the transformed variable is nearly symmetrically distributed. The large sample properties of an M-estimator of transformation parameter that is obtained by minimizing the integrated square of the imaginary part of the empirical characteristic function are investigated when a random sample is selected from some unspecified distribution. According to influence function calculations and Monte Carlo simulations, these estimates are less sensitive, than the normal model maximum likelihood estimates, to a few outliers.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.563-572
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• 2011

In this paper, the Lie symmetry analysis is performed on the three mixed second-order PDEs, which arise in fluid dynamics, nonlinear wave theory and plasma physics, etc. The symmetries and similarity reductions of the equations are obtained, and the exact solutions to the equations are investigated by the dynamical system and power series methods. Then, the exact solutions to the general types of PDEs are considered through a variable transformation. At last, the symmetry and integration method is employed for reducing the nonlinear ODEs.