• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.51-61
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• 2020

The study aims to compare whether using Earnings Response Coefficient (ERC) is better than using the new concept of Accounting Earnings Response Coefficient (AERC) in determining the earnings quality response coefficient value. Also, the study seeks to explain the effect of company characteristics and corporate governance on AERC through voluntary disclosure and information asymmetry. Research samples include 69 manufacturing companies listed on the Indonesian Stock Exchange over the period 2014-2017. The data come from annual reports, stock market prices, CSPI, EPS, stock returns and market returns. The research model is tested using the structural equation model (SEM) with partial least square (PLS). The results showed the value of the earnings response coefficient produced by AERC and ERC was different. Earnings quality resulting from AERC regression by adding CFO values better reflects the actual earnings quality. These results are consistent with the concept built from the proposition about earnings quality at AERC, that quality earnings are informative accounting earnings. The theoretical findings of this study provide an explanation that operational cash flow plays a role in evaluating earnings quality, while providing reinforcement that the ERC regression model fails to detect stock market reactions to information relevant to the aggregated values of accounting earnings.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1167-1177
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• 2017

The censored regression using the pseudo-response variable proposed by Buckley and James has been one of the most well-known models. Recently, the varying coefficient regression model has received a great deal of attention as an important tool for modeling. In this paper we propose a censored varying coefficient regression model using Buckley-James method to consider situations where the regression coefficients of the model are not constant but change as the smoothing variables change. By using the formulation of least squares support vector machine (LS-SVM), the coefficient estimators of the proposed model can be easily obtained from simple linear equations. Furthermore, a generalized cross validation function can be easily derived. In this paper, we evaluated the proposed method and demonstrated the adequacy through simulate data sets and real data sets.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1131-1134
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• 2003

Unknown parameters of a nonlinear system were estimated using a signal compression method. The estimated parameters were natural frequency and tile damping coefficient. This study applied a algorithm using tile comparison of the cross-correlation coefficient between the impulse response from a model and it from the signal compression method. The impulse through linear element included in a nonlinear system could be obtained by the signal compression method. The unknown parameters of the linear element could be estimated by comparing the Bode plots of system's impulse response with them of model's response. In this study, a LSCM(LabVIEW-Signal-Compression-Method) was developed to identify a nonlinear system. The LSCM consisted of National Instrument's (NI) Data Acquisition (DAQ) Board (Model PCI-1200), a monitoring program using LabVIEW software package, DAQ Signal Accessory Board, and 2nd-order electric circuits. The designed electric circuits consisted of resistors, inductors and capacitors. To evaluate the performance of the LSCM, the response from model with known parameters is compared with the response from the real system using the monitoring program. The results from simulation of experiment showed that the developed LSCM provided a reliable estimation performance.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.313-322
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• 2005

In this paper, we discuss suppression for logistic regression model. Suppression for linear regression model was defined as the relationship among sums of squared for regression as well as correlation coefficients of. variables. Since it is not common to obtain simple correlation coefficient for binary response variable of logistic model, we consider cumulative logistic models with multinomial and ordinal response variables rather than usual logistic model. As number of category of a response variable for the cumulative logistic model gets collapsed into binary, it is found that suppressions for these logistic models are changed. These suppression results for cumulative logistic models are discussed and compared with those of linear model.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.1
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• pp.81-90
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• 1999

The performance evaluation technique of a heat exchanger is described by using a transient response analysis for the determination of an average heat transfer coefficient. The model using a finite difference method can accommodate arbitrary inlet fluid temperature as well as longitudinal conduction. Temperature histories are obtained from the experiments at the inlet and outlet of test core. Heat transfer coefficient and friction factor of the plate array are obtained in short times using the data reduction program of transient response analysis in the single-blow method. The results agree very well with theoretical results. It is shown that the rms deviations are very small and the performance evaluation technique gives rapid and accurate results.

• Analyses & Alternatives
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• v.5 no.1
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• pp.3-24
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• 2021

This paper introduces a multilevel item-response-theory (IRT) model as a unifying model for hypothesis testing using legislative voting data. This paper shows that a probit or logit model is a special type of multilevel IRT model. In particular, it is demonstrated that, when a probit or logit model is applied to multiple votes, it makes unrealistic assumptions and produces incorrect coefficient estimates. The advantages of a multilevel IRT model over a probit or logit model are illustrated with a Monte Carlo experiment and an example from the U.S. House. Finally, this paper provides a practical guide to fitting this model to legislative voting data.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.7
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• pp.72-78
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• 2008

The line-of-sight(LOS) stabilization system is a precision electro-mechanical gimbals assembly for suppressing vibration due to its environment and tracking the target in a desired direction. This paper describes the design of gimbals system to reject the disturbance and to improve stabilization. The controller consists of a DSP with transducer and actuator interfaces. Unknown parameters of the gimbals are estimated by the signal compression method. The cross-correlation coefficient between the impulse response from the assumed model and the one from model of the gimbals is used to obtain the better estimation. The quasi-impulse response through linear element included in the gimbals could be obtained by the signal compression method. The unknown parameter of the linear element could be estimated as comparing the bode plots for impulse response from gimbals with them from model's response.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.2
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• pp.174-179
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• 2010

In order to interpret yield response of sugar beet to nitrogen fertilizer, and pig manure compost in saline-sodic soil of reclaimed tidal land, 4 kinds of response model, i.e., quadratic, exponential, square root, and linear response, and plateau model, are applied. The root fresh yield of sugar beet decreased exponentially with the increase of soil EC. The root fresh yield of sugar beet to nitrogen fertilizer was fitted best to the linear response, and plateau model among 4 yield response models with highly significant determination coefficient ($R^2=0.92^{**}$). The optimum N rate determined on the model was 138 kg N $ha^{-1}$. The root fresh yield of sugar beet to pig manure compost was fitted best to the quadratic model among 4 yield response models with highly significant determination coefficient ($R^2=0.99^{**}$). The maximum N rate determined on the model was 9.17 ton $ha^{-1}$. In conclusion, the proper model to interpret the yield of sugar beet in saline-sodic soil differs with the kinds of nutrient, linear response, and plateau model for fertilizer nitrogen, and quadratic model to pig manure compost.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.193-200
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• 2000

Numerical analysis of slope stability is presented using slice method, static seismic analysis methods, and earthquake response analysis methods. Static seismic force is considered as 0.2g while vertical static seismic force is not considered in analysis. For earthquake response analysis, Hachinohe-wave is applied. Safety factor calculated using slice method for failure surface. Calculating methods are Bishop's method and Janhu's method. Static seismic analysis was applied using Mhor-Coulomb model and earthquake response analysis was applied using non-linear elastic model.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.491-500
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• 2020

The present study proposes a time domain model for the Vortex-induced Vibration (VIV) simulation of a catenary riser under the combination of the current and oscillatory flow induced by vessel motion. In this model, the hydrodynamic force of VIV comprises excitation force, hydrodynamic damping and added mass, which are taken as functions of the non-dimensional frequency and amplitude ratio. The non-dimensional frequency is related with the response frequency, natural frequency, lock-in range and the fluid velocity. The relatively oscillatory flow induced by vessel motion is taken into account in the fluid velocity. Considering that the added mass coefficient and the non-dimensional frequency can affect each other, an iterative analysis is conducted at each time step to update the added mass coefficient and the natural frequency. This model is in detail validated against the published test models. The results show that the model can reasonably reflect the effect of the added mass coefficient on the VIV, and can well predict the riser's VIV under stationary and oscillatory flow induced by vessel motion. Based on the model, this study carries out the VIV simulation of a catenary riser with harmonic vessel motion. By analyzing the bending moment near the touchdown point, it is found that under the combination of the ocean current and oscillatory flow the vessel motion may decrease the VIV response, while increase the excited frequencies. In addition, the decreasing rate of the VIV under vessel surge is larger than that under vessel heave at small vessel motion velocity, while the situation becomes opposite at large vessel motion velocity.