• Journal of IKEEE
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• v.23 no.3
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• pp.817-825
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• 2019

Difference equation is useful for control algorithm in the microprocessor. To approximate a derivative values from sampled data, it is used the methods of forward, backward and central differences. The key of computing discrete derivative values is the finite difference coefficient. The focus of this paper is a new approach method of finite difference formula. And we apply the proposed method to the recursive least squares(RLS) algorithm.

• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.315-327
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• 2021

The Spatial Autoregressive (SAR) models have drawn considerable attention in recent econometrics literature because of their capability to model the spatial spill overs in a feasible way. While considering the Bayesian analysis of these models, one may face the problem of lack of robustness with respect to underlying prior assumptions. The generalized Bayes estimators provide a viable alternative to incorporate prior belief and are more robust with respect to underlying prior assumptions. The present paper considers the SAR model with a set of linear restrictions binding the regression coefficients and derives restricted generalized Bayes estimator for the coefficients vector. The minimaxity of the restricted generalized Bayes estimator has been established. Using a simulation study, it has been demonstrated that the estimator dominates the restricted least squares as well as restricted Stein rule estimators.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.273-289
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• 2023

In this paper, we develop a new time series model for predicting IPO (initial public offering) data with non-negative integer value. The proposed model is based on integer-valued autoregressive (INAR) model with a Poisson thinning operator. Just as the heterogeneous autoregressive (HAR) model with daily, weekly and monthly averages in a form of cascade, the integer-valued heterogeneous autoregressive (INHAR) model is considered to reflect efficiently the long memory. The parameters of the INHAR model are estimated using the conditional least squares estimate and Yule-Walker estimate. Through simulations, bias and standard error are calculated to compare the performance of the estimates. Effects of model fitting to the Korea's IPO are evaluated using performance measures such as mean square error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) etc. The results show that INHAR model provides better performance than traditional INAR model. The empirical analysis of the Korea's IPO indicates that our proposed model is efficient in forecasting monthly IPO volumes.

• Archives of Pharmacal Research
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• v.3 no.1
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• pp.37-49
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• 1980

Chlorpropamide, $C_{10}H_{13}N_{2}O_{3}SCI$, forms orthofombic crystals of space group $P_{2}_{ 1}2_{1}2_{1}$ with a 9.066 $\pm$ 0.004, b = 5.218 $\pm$ 0.003, c = 26, 604 $\pm$, 0.008 $\AA$, and four molecules per cell. Three dimensional photographic data were collected with Mo-K$\alpha$ radiation. The structure was determined using Patterson, Fourier and Difference syntheses methods and refined by the block-diagonal least-squares methods with anisotropic thermal parameters for all nonhydrogen atoms and isotropic thermal parameters for all hydrogen atomes. The final R value was 0.10 for the 1823 observed independent reflections. The dihedral angle between the planes through the benzene ring and the urea goup is 99$^{\circ}$. The conformational angle formed by the projection of the S-C(1) with that of N(1)-C(7) when the projection is taken along the S-N(1) bond is 76$^{\circ}$. The molecule appears to form with neighbouring molecules two hydrogen bonds, N(1)..H...O(3) and N(2)-H...0(2) of lengths 2.774 and 2.954$\AA$ respectively related by screw diads parallel to the a axis. Adjacent molecules parallel to b and c axis are bound together by van der Wasls forces.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.7-13
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• 2012

This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.

• Journal of computational fluids engineering
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• v.13 no.1
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• pp.49-56
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• 2008

Chimera grid methods have been widely used in Computational Fluid Dynamics due to its simplicity in constructing grid systems over complex bodies, and suitability for unsteady flow computations with bodies in relative motion. However, the interpolation procedure for ensuring the continuity of the solution over overlapped regions fails when the so-called orphan cells are present. We have adopted the MLS(Moving Least Squares) method to replace commonly used linear interpolations in order to alleviate the difficulty associated with the orphan cells. MLS is one of the interpolation methods used in mesh-less methods. A number of examples with MLS are presented to show the validity and the accuracy of the method.

• Journal of computational fluids engineering
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• v.14 no.4
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• pp.93-100
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• 2009

The gridless (or meshfree) methods, such as MPS, SPH, FPM an so forth, are feasible and robust for the problems with moving boundary and/or complicated boundary shapes, because these methods do not need to generate a grid system. In this study, a gridless solver, which is based on the combination of moving least square interpolations on a cloud of points with point collocation for evaluating the derivatives of governing equations, is presented for two-dimensional unsteady incompressible Navier-Stokes problem in the low Reynolds number. A MAC-type algorithm was adopted and the Poission equation for the pressure was solved successively in the moving least square sense. Some typical problems were solved by the presented solver for the validation and the results obtained were compared with analytic solutions and the numerical results by conventional CFD methods, such as a FVM.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.111-117
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• 1997

The ordinary least squares estimator $S^2$ for the variance of the disturbances is considered in the linear regression model with sutocorrelated disturbances. It is proved that the OLS-estimator of disturbance variance is asymptotically unbiased and weakly consistent, when the distrubances are generated by an MA(q) process. In particular, the asymptotic unbiasedness and consistency of $S^2$ is satisfied without any restriction on the regressor matrix.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.288-295
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• 1995

In this paper a hypotheses test procedure based on the least absolute deviation estimators for the unknown parameters in nonlinear regression models is investigated. The asymptotic distribution of the proposed likelihood ratio test statistic are established voth under the null hypotheses and a sequence of local alternative hypotheses. The asymptotic relative efficiency of the proposed test with classical test based on the least squares estimator is also discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.2
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• pp.41-47
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• 1998

We consider some numerical solution methods for equality-constrained quadratic problems in the context of structural analysis. Sparse orthogonal schemes for linear least squares problem are adapted to handle the solution step of the force method. We also examine these schemes with substructuring concepts.