• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2532-2537
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• 2005

FIR(Finite Impulse Response) filter is well known to be ideal for the finite time state-space model, but it requires much computation due to its inherent non-recursive structure especially when the measurement interval grows to a large extent. And often a fixed-lag smoother based on the finite time interval is needed to monitor the soundness of the system model and the measurement model, but the computation burden of FIR-type smoother imposes much restriction of its usage for real-time application. Conventional recursive forms of FIR estimator[1]-[4] could not be used for real time applications, since they are numerically unstable in their recursive equations. To cope with this problem, we suggest a stable recursive form FIR estimator(SRFIR) and its usefulness is demonstrated for designing the real-time fixed-lag smoother on the finite time window through an example of detection of rate bias in the anti-aircraft gun fire control system.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.481-487
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• 2000

When we construct an interval estimate of two independent proportions with rare events, the standard approach based on the normal approximation behaves badly in many cases. The problem becomes more severe when no success observations are observed on both groups. In this paper, we compare two alternative methods of constructing a confidence interval of the difference of two independent proportions by use of simulation. One is based on the profile likelihood and the other is the Bayesian probability interval. It is shown in this paper that the Bayesian interval estimator is easy to be implemented and performs almost identical to the best frequentist's method -the profile likelihood approach.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.191-204
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• 2003

The target costing technique, mathematically discussed by Sauers, only uses the $C_p index along with Taguchi loss function and $\bar{X}$-P control charts to setup goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p value to $\bar{X}$-P control charts to obtain goal control limits. Studies have shown that the point estimator of the $C_p index, $C_p, could vary from time to time due to the sampling error. The suggested approach is to use confidence intervals, especially the lower confidence intervals, to replace the point estimator. Therefore, an improvement on target costing technique is presented by applying the lower confidence interval of the $C_p index and using both Taguchi and Spiring's loss functions together with $\bar{X}$-P charts to make this technique more robust in practice. An example is also provided to illustrate how the improved target costing technique works.

• Journal of the Korean Statistical Society
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• v.28 no.1
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• pp.93-106
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• 1999

In this paper we consider estimation of a real valued parameter in the drift coefficient of a Hilbert space valued Ito stochastic differential equation. First we consider observation of the corresponding diffusion in a fixed time interval [0, T] and prove the Bernstein - von Mises theorem concerning the convergence of posterior distribution of the parameter given the observation, suitably normalised and centered at the MLE, to the normal distribution as Tlongrightarrow$\infty$. As a consequence, the Bayes estimator of the drift parameter becomes asymptotically efficient and asymptotically equivalent to the MLE as Tlongrightarrow$\infty$. Next, we consider observation in a random time interval where the random time is determined by a predetermined level of precision. We show that the sequential MLE is better than the ordinary MLE in the sense that the former is unbiased, uniformly normally distributed and efficient but is latter is not so.

• Bulletin of the Korean Mathematical Society
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• v.44 no.2
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• pp.247-257
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• 2007

Consider the heteroscedastic regression model $Y_i=g(x_i)+{\sigma}_i\;{\epsilon}_i=(1{\leq}i{\leq}n)$, where ${\sigma}^2_i=f(u_i)$, the design points $(x_i,\;u_i)$ are known and nonrandom, and g and f are unknown functions defined on closed interval [0, 1]. Under the random errors $\epsilon_i$ form a sequence of NA random variables, we study the asymptotic normality of wavelet estimators of g when f is a known or unknown function.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.281-288
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• 2015

In this paper, the maximum likelihood estimators and confidence intervals for parameters of Weibull distribution are derived under three level constant stress accelerated life tests and the assumption that a log quadratic relationship exits between stress and the scale parameter ${\theta}$. The compound linear plan proposed by Kim (2006) is used to allocate the test units at each stress level, which performed nearly as good as the optimum quadratic plan and had the advantage of simplicity. Some simulation studies are given.

• Journal of Korean Society for Quality Management
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• v.30 no.1
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• pp.144-151
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• 2002

Consider the problem of estimating the confidence interval of defect rate of a specified population through a screening test. Relationship between defect rate of the population and sensitivity and specificity of the screening test is discussed. More general statistical problem is introduced with the assumption of unknown imperfect specificity. An improved version of Hogan & Gladden(1978)'s estimator is proposed and discussed. Simulation studies are performed to compare the efficiency of the proposed estimator with current estimators.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.66-72
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• 2003

In the present paper some fundamentals about exceeding the guard interval of an OFDM system is going to discuss and will introduce method to cancel a ISI and ICI effects. In this paper, the performance characteristics of robust OFDM receiving system algorithm that is composed of a channel estimator using recursive least square(RLS) algorithm in time domain and of a ISI and ICI replica and subtracter using the channel coefficients are presented. By computer simulation method, the effect of suppression of ISI and ICI is demonstrated and compared the BER performance with a conventional 1-tap equalized system. Especially the presented scheme improves the BER performance at low SNRs more or so compared with the conventional one-tap equalized receiving configuration.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.833-842
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• 2014

Non-inferiority trials indicate whether the effect of an experimental treatment is not worse than an active control. Chen et al. (2006) and Kang (2010) proposed a test method for non-inferiority trials using confidence intervals. In this paper, we suggest a new nonparametric method using a confidence interval based on Wilcoxon rank-sum test and Hodges-Lehmann estimator of active control. A Monte-Carlo simulation study compares the type I error and the power of the proposed method with previous methods.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.365-376
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• 2020

Interval-valued data, a type of symbolic data, is given as an interval in which the observation object is not a single value. It can also occur frequently in the process of aggregating large databases into a form that is easy to manage. Various regression methods for interval-valued data have been proposed relatively recently. In this paper, we introduce a nonparametric regression model using the kernel function and a nonlinear regression model for the interval-valued data. We also propose applying the local linear regression model, one of the nonparametric methods, to the interval-valued data. Simulations based on several distributions of the center point and the range are conducted using each of the methods presented in this paper. Various conditions confirm that the performance of the proposed local linear estimator is better than the others.