• Journal of the Korean Data and Information Science Society
• /
• v.20 no.2
• /
• pp.321-328
• /
• 2009

In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.6 no.4
• /
• pp.21-37
• /
• 2011

The purpose of this article is to analyze the relationship between corporate firm performance and large shareholder ownership. We use the individual firms listed in KOSDAQ and implement the ordinary least squares regression analysis. Our empirical analysis shows that the relationship between large shareholder ownership and market performance is not in accordance with the preceding studies supporting U type. We document, however, that the empirical analysis shows that the relationship between large shareholder ownership and accounting performance is similar to the reverse U type. A robustness test is implemented to generate a more acute analysis. The robustness test shows that the large shareholder's shareholding of 0-50% supports the interest convergence hypothesis; however, more than 50% of the shareholding shows that the large shareholder ownership is not significantly related to the accounting performance.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.29 no.3
• /
• pp.237-244
• /
• 2016

This paper presents a nonlinear Moving Least Squares(MLS) difference method for material nonlinearity problem. The MLS difference method, which employs strong formulation involving the fast derivative approximation, discretizes governing partial differential equation based on a node model. However, the conventional MLS difference method cannot explicitly handle constitutive equation since it solves solid mechanics problems by using the Navier's equation that unifies unknowns into one variable, displacement. In this study, a double derivative approximation is devised to treat the constitutive equation of inelastic material in the framework of strong formulation; in fact, it manipulates the first order derivative approximation two times. The equilibrium equation described by the divergence of stress tensor is directly discretized and is linearized by the Newton method; as a result, an iterative procedure is developed to find convergent solution. Stresses and internal variables are calculated and updated by the return mapping algorithm. Effectiveness and stability of the iterative procedure is improved by using algorithmic tangent modulus. The consistency of the double derivative approximation was shown by the reproducing property test. Also, accuracy and stability of the procedure were verified by analyzing inelastic beam under incremental tensile loading.

• Smart Structures and Systems
• /
• v.25 no.5
• /
• pp.569-580
• /
• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.8
• /
• pp.32-41
• /
• 1999

In this paper, an inversion method using chirp signals and two near field receivers is proposed. Inversion problems can be formulated into the probabilistic models composed of signals, a forward model and noise. Forward model to simulate chirp signals is chosen to be the source-wavelet-convolution planewave modeling method. The solution of the inversion problem is defined by a posteriori pdf. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the ranges for a priori uniform distribution is based. The genetic algorithm can be applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L₂norm of the difference between measured and modeled signals. The observed signals can be separated into a set of two signals reflected from the upper and lower boundaries of a sediment. The separation of signals and successive applications of the genetic algorithm optimization process reduce the search space, therefore improving the inversion results. Not only the marginal pdf but also the statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm. The examples applied here show that, for synthetic data with noise, it is possible to carry out an inversion for sedimentary layers using the proposed inversion method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.28 no.10
• /
• pp.810-818
• /
• 2017

This paper presents the approaching target above ground tracking based on Kalman filter applied to the proximity sensor for the active defense system. The proximity sensor located on the front of the countermeasure is not easy to detect when the anti-tank threat enters a fragment dispersion range due to limited antenna beamwidth. In addition, it is difficult for the proximity sensor to detect the anti-tank threat accurately at a terrestrial environment including various clutters. To solve these problems, this study presents the approaching target above ground tracking based on Kalman filter and applies the novel estimation method for a noise covariance matrix to improve a tracking performance. Then, a high tracking performance of Kalman filter applied the proposed noise covariance matrix is presented through field firing test results and the validity of the proposed study is examined.

• Journal of Korean Society of Forest Science
• /
• v.79 no.3
• /
• pp.260-268
• /
• 1990

Two types of ridge regression estimators were compared with the ordinary least squares (OLS) estimator in order to select the "best" estimator when multicollinearitc existed. The ridge estimators were Mallows's (1973) $C_P$-like statistic, and Allen's (1974) PRESS-like statistic. The evaluation was conducted based on the predictive ability of a yield model developed by Matney et al. (1988). A total of 522 plots from the data of the Southwide Loblolly Pine Seed Source study was used in this study. All of ridge estimators were better in predictive ability than the OLS estimator. The ridge estimator obtained by using Mallows's statistic performed the best. Thus, ridge estimators can be recommended as an alternative estimator when multicollinearity exists among independent variables.

• Journal of Korea Trade
• /
• v.25 no.6
• /
• pp.57-77
• /
• 2021

Purpose - International strategic alliance has been regarded as a strategic decision made by firms' managerial problems and ensure performance growth. From the perspective of the proactive behavior for changing strategies in a global market, this study aims to identify whether performance feedback influences firms' decisions to pursue strategic alliances. This study examines the effects of performance feedback on performance when firms use strategic alliances. Design/methodology - To analyze the impact of performance feedback on forming an international strategic alliance, this study adopt the concept of performance feedback to develop a research model and our hypotheses. Thus, this study used a two-stage least squares unbalanced panel data analysis with random effects. This study is based on 24,543 observations from Korean manufacturing firms from 2007 to 2016. Findings - The results show that firms pursue the formation of strategic alliances more actively, if their past financial and R&D performance are lower than their aspiration level, based on the result of performance feedback. An in split sample analysis for examining the effect of a firm's technology sophistication based on the OECD's classification, negative innovation performance discrepancy has positive effects on the probability of international alliance in high-tech and medium-high-tech industries. Financial performance also improves when a firm decides to form a strategic alliance based on the results of performance feedback. Originality/value - This research extends recent efforts to better understand the effect of performance feedback on firms' performance when they use strategic alliances. These findings suggest that the CEOs and managers of firms should consider the performance feedback perspective when deciding to pursue a strategic alliance to improve performance. In other words, the decision-makers in a firm must analyze and consider various complex variables inside and outside the firm and expand such subjects of examination to more complex and dynamic factors.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.3
• /
• pp.147-152
• /
• 2023

This paper is a study of a linear algebra course taught in a high school on-demand course. Compared to the regular course, flipped learning was added to the course, and applications to signal processing related problems were covered in consideration of students' career aspirations. Overall, the class was a mixture of traditional lectures and flipped learning. Flipped learning was implemented twice. The flipped class consisted of pre-class, in-class and post-class. To verify the effectiveness of the course, a survey was conducted and most of the evaluation items were above 4. The topics of the flipped learning were Markov chains and least squares problem, which are very important in the field of signal processing.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.37 no.1
• /
• pp.41-47
• /
• 2024

This paper utilizes computational asymptotic analysis to compute the boundary layer solution for composite beams and validates the findings through a comparison with ANSYS results. The boundary layer solution, presented as a sum of the interior solution and pure boundary layer effects, necessitates a mathematically rigorous formalization for both interior and boundary layer aspects. Computational asymptotic analysis emerges as a robust technique for addressing such problems. However, the challenge lies in connecting the boundary layer and interior solutions. In this study, we systematically separate the principles of virtual work and the principles of Saint-Venant to tackle internal and boundary layer issues. The boundary layer solution is articulated by calculating the Papkovich-Fadle eigenfunctions, representing them as linear combinations of real and imaginary vectors. To address warping functions in the interior solutions, we employed a least squares method. The computed solutions exhibit excellent agreement with 2D finite element analysis results, both quantitatively and qualitatively. This validates the effectiveness and accuracy of the proposed approach in capturing the behavior of composite beams.