• Communications for Statistical Applications and Methods
• /
• v.24 no.5
• /
• pp.493-505
• /
• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Communications for Statistical Applications and Methods
• /
• v.12 no.2
• /
• pp.443-451
• /
• 2005

The studied in this paper is a new algorithm for searching the maximum likelihood estimate(MLE) in which probability density function is not explicitly expressed. Newton-Raphson's root-finding routine and a nonlinear numerical optimization algorithm with constraint (so-called feasible sequential quadratic programming) are used. This algorithm is applied to the Wakeby distribution which is importantly used in hydrology and water resource research for analysis of extreme rainfall. The performance comparison between maximum likelihood estimates and method of L-moment estimates (L-ME) is studied by Monte-carlo simulation. The recommended methods are L-ME for up to 300 observations and MLE for over the sample size, respectively. Methods for speeding up the algorithm and for computing variances of estimates are discussed.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.1
• /
• pp.32-37
• /
• 2020

This paper proposes a new l₁-norm-Recursive Least Squares (RLS) algorithm which is numerically more robust than the conventional l₁-norm-RLS. The l₁-norm-RLS was proposed by Eksioglu and Tanc in order to estimate the sparse acoustic channel. However the algorithm has numerical instability in the inverse matrix calculation. In this paper, we propose a new algorithm which is robust against the numerical instability. We show that the proposed method improves stability under several numerically erroneous situations.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.39 no.3
• /
• pp.241-247
• /
• 2015

Deflection and deformation occur easily in structures with long length, such as bridges and pipelines. Shape monitoring is required for ensuring their structural health. A fiber Bragg grating (FBG) sensor can be used for monitoring a large-scale structure because of its advantage of multiplexing. In this study, FBG sensors were used for monitoring a composite beam structure, and its strains were measured at multiple points. Thereafter, a shape estimation technique based on the strains was studied. Particularly, a three-dimensional shape estimation technique was proposed for accurate structural health monitoring. A simple experiment was conducted to verify the performance of the shape estimation technique. The result revealed that the estimated shape of the composite beam structure was in agreement with the actual shape obtained after the deformation of the specimen. Additionally, the deflection at a specific point was verified by comparing the estimated and actual deformations measured using a micrometer.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2001.10a
• /
• pp.324-329
• /
• 2001

The destructive method is reliable and widely used for the estimation of material degradation but, it have time-consuming and a great difficulty in preparing specimens from in-service industrial facilities. Therefore, the estimation of degraded structural materials by nondestructive evaluation is strongly desired. In this paper, the use of guided wave was suggested for the evaluation of thermally damaged 2.25 Cr-lMo steel as an alternative way to compensate for limitations of fracture tests. The observation of microstructure variations of the material including carbide precipitation increase and spheroidization near grain boundary was conducted and the correlation with the guided wave features such as energy loss ratio and group velocity changes was investigated. Through this study, the feasibility of ultrasonic guided wave evaluation for thermally damaged materials was explored.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.526-526
• /
• 2000

The present has a double objective. The first one is to compare and estimate sixteen continuous-time methods through the identificatiun of a system consisted with an RLC electrical circuit. These sixteen methods are classified into three groups that are the linear filters, the modulating functions and the integral methods. The second objective is to estimate directly the physical parameters of the RLC circuit, without resorting to a discrete-time model. The system is consisted of a coil with inductance L and resistance H, and of a capacitor with capacitance C. Having written the physical equations which describe the behavior of the system, the transfer function in where the initial conditions appear is given. These initial conditions should be taken into account during the parameter estimation phase, because they are inevitable within the framework of real signals. A physical interpretation of the identified models is tempted by the direct estimation of the physical parameters L and C. In conclusion, a classification of the studied methods is proposed.

• Journal of the Korean Statistical Society
• /
• v.26 no.4
• /
• pp.445-452
• /
• 1997

A more generalized version of the information inequality based on diffusivity which is a natural measure of dispersion for median-unbiased estimators developed by Sung et al. (1990) is presented. This non-Bayesian L$_{1}$ information inequality is free from regularity conditions and can be regarded as an analogue of the Chapman-Robbins inequality for mean-unbiased estimation. The approach given here, however, deals with a more generalized situation than that of the Chapman-Robbins inequality. We also develop a Bayesian version of the L$_{1}$ information inequality in median-unbiased estimation. This latter inequality is directly comparable to the Bayesian Cramer-Rao bound due to the van Trees inequality.

• Journal of KSNVE
• /
• v.10 no.5
• /
• pp.769-774
• /
• 2000

The purpose of the work is to present successful applications of a modified wavelet shrinkage method for the accurate and fast estimation of a transfer function. Although the experimental process of determining a transfer function introduces not only Gaussian but also non-Gaussian noises, most existing estimation methods are based only on a Gaussian noise model. To overcome this limitation, we propose to employ a modified wavelet shrinkage method in which L1 -based median filtering and L2 -based wavelet shrinkage are applied repeatedly. The underlying theory behind this approach is briefly explained and the superior performance of this modified wavelet shrinkage technique is demonstrated by a numerical example.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1283-1285
• /
• 1996

This paper proposed frequency estimation the method of distorted sinusoidal signals by harmoics. An approximate estimation based on FFT and the accurate basic frequency was estimated by proposed method with Fourer Series, and the harmonics were estimated by the basic frequency. The sinusoidal signals is extracted by filter banks based on the estimated hamonics. The rate of basic and hamonics power is estimated by the extracted sinusoidal signals and we developed their algorithm and programs.

• The Korean Journal of Applied Statistics
• /
• v.4 no.2
• /
• pp.129-135
• /
• 1991

A few simple methods to find $L_1$-unbiased estimators for location and scale parameters are summarized and examples utilizing diffusivity, a natural measure of dispersion for $L_1$-unbiased estimators, are given.