• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.61-77
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• 2011

One of the most important problems in the estimation of the parameter of the failure model, is the cost of experimental sampling units, which can be reduced by using any prior information available about ${\theta}$, and devising a two-stage pooling shrunken estimation procedure. We have proposed an estimator of the reliability function (R(t)) of the exponential model using two-stage time censored data when a prior value about the unknown parameter (${\theta}$) is available from the past. To compare the performance of the proposed estimator with the classical estimator, computer intensive calculations for bias, mean squared error, relative efficiency, expected sample size and percentage of the overall sample size saved expressions, were done for varying the constants involved in the proposed estimator (${\tilde{R}}$(t)).

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.101-106
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• 1997

In this paper, sample selective RLS(SSRLS) method is proposed, which aims to eliminate the influence of pitch bias. Its basic concepts are as follows. First it extracts the open glottis interval by using the residual signals, then estimates the formant values from the selected speech samples excluding above open glottis interval. This method has some analogy with the SSLPS, the simulation is conducted upon the synthetic and real speech. From these results, we find more usefulness of the proposed method than the conventional ones.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2011-2013
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• 2001

In this paper the MMAE(Multiple Model Adaptive Estimation) algorithm using the MGEKF(Modified Gain Extended Kalman Filter) of which modes are set to be measurement biases is proposed to enhance the performance of target tracking with bearing only measurements. The state are composed of relative position, relative velocity and taregt acceleration. The mode probability is calculated from the bearing only measurements from the HMS(Hull-Mounted Sonar). The proposed algorithm is tested in a series of computer simulation runs.

• International Journal of Reliability and Applications
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• v.14 no.2
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• pp.79-96
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• 2013

Exponential distribution plays a key role in engineering reliability and its applications. The exponential failure model has been studied for years. This article introduces two new preliminary test estimators for the reliability function (R(t)) in complete and censored samples from the exponential model with the use of a prior estimation (${\theta}_0$) of the mean (${\theta}$). The proposed preliminary test estimators are studied and compared numerically with the existing estimators. Computer-intensive calculations for bias and relative efficiency show that for, different values of levels of significance and for varying constants involved in the proposed estimators, the proposed estimators are far better than classical and existing estimators.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.53-64
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• 2022

High dimensional time series is gaining considerable attention in recent years. The sparse vector heterogeneous autoregressive (VHAR) model proposed by Baek and Park (2020) uses adaptive lasso and debiasing procedure in estimation, and showed superb forecasting performance in realized volatilities. This paper extends the sparse VHAR model by considering non-convex penalties such as SCAD and MCP for possible bias reduction from their penalty design. Finite sample performances of three estimation methods are compared through Monte Carlo simulation. Our study shows first that taking into cross-sectional correlations reduces bias. Second, nonconvex penalties performs better when the sample size is small. On the other hand, the adaptive lasso with debiasing performs well as sample size increases. Also, empirical analysis based on 20 multinational realized volatilities is provided.

• Asia Marketing Journal
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• v.21 no.1
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• pp.65-87
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• 2019

Most studies on how people perceive a given quantity of items were conducted with visual cues exclusively and only offered spatial area based explanations, such as spatial estimation and perceptual grouping theories. This article establishes how people perceive a given quantity when only a written description is provided without any visual cues. Across two studies we show that variety decreases perceived quantity when a variety cue is given, while variety increases perceived quantity when a visual cue is not given. This is because people tend to rely heavily on spatial areas when a visual cue is present and because people are prone to confirmation bias when they are provided with no visual cues but only written descriptions. Furthermore, we highlight that quantity perception has a mediation effect on consumers' attitude-the intention to participate in sales promotional events. Lastly, we summarize the article and discuss its contributions, implications, limitations, and suggestions for future research.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.65-74
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• 1994

In the steady-state simulation, it is important to identify initialization bias for the correct estimates of the simulation model under study. In this paper, the methods from chaos theory are applied to the determination of truncation points in the simulation data for controlling the initial bias. Two methods are proposed and evaluated based on their effectiveness for estimation the average waiting time in M/M/1($\infty$) queueing model.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.535-545
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• 2015

In a various range of applications including hydrology, the type-I extreme value distribution has been extensively used as a probabilistic model for analyzing extreme events. In this paper, we introduce methods for estimating the scale parameter of the type-I extreme value distribution. A simulation study is performed to compare the estimators in terms of mean-squared error and bias, and the obtained results are provided.

• Environmental and Resource Economics Review
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• v.10 no.4
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• pp.515-545
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• 2001

This paper introduces the least absolute deviations estimation of the contingent valuation model, which corresponds to the semi-parametric estimation of discrete choice models by Manski (1975, 1985) and Lee (1992). The least absolute deviations estimation is more robust to mis-specified distributional assumptions in the estimation of the contingent valuation model, compared to the maximum likelihood estimation. The full identification and strong consistency of the estimation are proved and its application to different formats of contingent valuation survey data is discussed. Simulation studies are designed to evaluate its operational characteristics including computational strategies, small sample properties and the efficiency gain of a follow-up question. The bias and efficiency of least absolute deviations and maximum likelihood estimation are compared in the presence of heteroskedasticity.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.395-400
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• 2006

Among the various error sources in positioning and navigation, the paper focuses on the modeling and prediction of receiver clock bias and then tries to achieve positioning based on simulated and predicted clock bias. With the SA off, it is possible to model receiver clock bias more accurately. We selected several types of GNSS receivers for test using ARMA model. To facilitate prediction with short and limited sample pseudorange observations, AR and ARMA are compared, and the improved AR model is presented to model and predict receiver clock bias based on previous solutions. Our work extends to clock bias prediction and positioning based on predicted clock bias using only 3 satellites that is usually the case under urban canyon situation. In contrast to previous experiences, we find that a receiver clock bias can be well modeled using adopted ARMA model. Test has been done on various types of GNSS receivers to show the validation of developed model. To further develop this work, we compare solution conditions in terms of DOP values when point positioning is conducted using 3 satellites to simulate urban positioning environment. When condition allows, height component is derived from other ways and can be set as known values. Given this condition, location is possible using less than 2 GNSS satellites with fixed height. Solution condition is also discussed for this background using mode of constrained positioning. We finally suggest an effective predictive time span based on our test exploration under varied conditions.