• The Korean Journal of Applied Statistics
• /
• v.24 no.3
• /
• pp.445-453
• /
• 2011

Almost all small area estimations are obtained by minimizing the mean squared error. Recently relative error prediction methods have been developed and adapted to small area estimation. Usually the estimators obtained by using relative error prediction is called a shrinkage estimator. Especially when data set consists of large range values, the shrinkage estimator is known as having good statistical properties and an easy interpretation. In this paper we study the shrinkage estimators based on logistic regression type estimators for small area estimation. Some simulation studies are performed and the Economically Active Population Survey data of 2005 is used for comparison.

• Communications for Statistical Applications and Methods
• /
• v.21 no.5
• /
• pp.435-444
• /
• 2014

The most widely used optimal bandwidth is known to minimize the mean integrated squared error(MISE) of a kernel density estimator from a true density. In this article proposes, we propose a bandwidth which asymptotically minimizes the mean integrated density power divergence(MIDPD) between a true density and a corresponding kernel density estimator. An approximated form of the mean integrated density power divergence is derived and a bandwidth is obtained as a product of minimization based on the approximated form. The resulting bandwidth resembles the optimal bandwidth by Parzen (1962), but it reflects the nature of a model density more than the existing optimal bandwidths. We have one more choice of an optimal bandwidth with a firm theoretical background; in addition, an empirical study we show that the bandwidth from the mean integrated density power divergence can produce a density estimator fitting a sample better than the bandwidth from the mean integrated squared error.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.1
• /
• pp.183-187
• /
• 2007

This paper proposes Fuzzy Speed Estimator using Fuzzy Logic Controller(FLC) as a adaptive law in Model Reference Adaptive System(MRAS) in order to realize the speed-sensorless control of an induction motor. Fuzzy Speed Estimator estimates the speed of an induction motor with a rotor flux of the reference model and the adjustable model in MRAS. Fuzzy logic controller reduces the error of the rotor flux between the reference model and the adjustable model using the error and the change of error of the rotor flux as the input of FLC. The experiment is executed to verify the propriety and the effectiveness of the proposed speed estimator.

• Journal of information and communication convergence engineering
• /
• v.8 no.3
• /
• pp.281-288
• /
• 2010

This paper investigates the performance of IEEE 802.11p wireless access in vehicular environments (WAVE) system in small-scale fading models reported by Georgia Institute of Technology (Georgia Tech). We redesign the small-scale fading models to be applied to the computer simulation and develop the IEEE 802.11p WAVE physical layer simulator to provide the bit error rate and packet error rate performances. Moreover, a new channel estimator using decision directed channel estimation and linear minimum mean square error smoothing is proposed in order to improve the performance of the conventional least square channel estimator using two identical long training symbols. The simulation results are satisfactorily coincident with the scenarios of Georgia Tech report, and the proposed channel estimator significantly outperforms the conventional channel estimator.

• Communications for Statistical Applications and Methods
• /
• v.16 no.4
• /
• pp.659-667
• /
• 2009

Recently Song and Cheon (2006) and Cheon and Lim (2009) developed the generalized maximum entropy(GME) estimator to solve ill-posed problems for the regression coefficients in the simple panel model. The models discussed consider the individual and a spatial autoregressive disturbance effects. However, in many application in economics the data may contain nested groupings. This paper considers a two-way error component model with nested groupings for the ill-posed data and proposes the GME estimator of the unknown parameters. The performance of this estimator is compared with the existing methods on the simulated dataset. The results indicate that the GME method performs the best in estimating the unknown parameters in terms of its quality when the data are ill-posed.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.6
• /
• pp.1223-1232
• /
• 2011

Tong and Wang's estimator (2005) is a new approach to estimate the error variance using least squares method such that a simple linear regression is asymptotically derived from Rice's lag- estimator (1984). Their estimator highly depends on the setting of a regressor and weights in small sample sizes. In this article, we propose a new approach via a local quadratic approximation to set regressors in a small sample case. We estimate the error variance as the intercept using a ridge regression because the regressors have the problem of multicollinearity. From the small simulation study, the performance of our approach with some existing methods is better in small sample cases and comparable in large cases. More research is required on unequally spaced points.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.7
• /
• pp.1332-1337
• /
• 2006

In this paper, a noble second stage hetero-estimator is used for positioning error detection in mobile robot. Previous methods are either expensive in the case of positioning error correction or not able to detect positioning error. To overcome the latter shortage, the positioning error detection is performed using second stage hetero-estimator in motor model of mobile robot without any additional costs. A Kalman filter in the estimator gets the residual of motor current and an adaptive self-tunning filter checks the whiteness of the residual. Some simulation results show the possibility of the proposed method.

• Communications for Statistical Applications and Methods
• /
• v.8 no.1
• /
• pp.15-27
• /
• 2001

One proposal is made for constructing nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of idea of Johns for estimating the center of the symmetric distribution together with the idea of regression quantiles and regression trimmed mean. This nonparametric estimator and some other L-estimators are studied by Monte Carlo.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.8C
• /
• pp.613-616
• /
• 2008

In this paper, a fine residual frequency offset estimation scheme is proposed for multiband orthogonal frequency division multiplexing ultra-wideband (MB-OFDM UWB) systems. The basic idea of our approach is based on the fact that two adjacent OFDM symbols carry the identical information in the MB-OFDM UWB system, thus removing the need of pilot symbols. The mean square error of the synchronization scheme is evaluated and simulation results are used to verify the effectiveness of the proposed estimator. When compared to the pilot-aided conventional estimator, the proposed estimator has a lower estimation error.

• Communications for Statistical Applications and Methods
• /
• v.6 no.1
• /
• pp.285-292
• /
• 1999

In this paper we propose the several estimators of the Lorenz curve in the Pareto distribution and obtain the bias and the mean squared error for each estimator. We compare the proposed estimators with the uniformly minimum variance unbiased estimator (UMVUE) and the maximum likelihood estimator (MLE) in terms of the mean squared error (MSE) through Monte Carlo methods and discuss the results.