• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.337-345
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• 1999

The long-tailed, positively skewed exponential distribution can be made into an almost symmetric distribution by taking the exponent of the data. In these situations, to use the traditional shewhart control limits on an individuals chart would be impractical and inconvenient. The transformed data, approximately bell-shaped, can be plotted conveniently on the individuals chart and exponentially weighted moving average chart. In this paper, using modifying statistics with transformed exponential of the data, we give a method for constructing control charts. Selecting method of exponent for individual chart is evaluated. And consider that smaller weight being assigned to the older data as time process and properties and taking method of exponent($\theta$), weighting factor($\alpha$) are suggested. Our recommendation, on the basis result of simulation, is practical method for EWMA chart.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.574-574
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• 2000

Consider the problem of estimating regression function from a set of data which is contaminated by a long-tailed error distribution. The linear smoother is a kind of a local weighted average of response, so it is not robust against outliers. The kernel M-smoother and the lowess attain robustness against outliers by down-weighting outliers. However, the kernel M-smoother and the lowess requires the iteration for computing the robustness weights, and as Wang and Scott(1994) pointed out, the requirement of iteration is not a desirable property. In this article, we propose the robust nonparametic regression method which does not require the iteration. Robustness can be achieved not only by down-weighting outliers but also by transforming outliers. The rank transformation is a simple procedure where the data are replaced by their corresponding ranks. Iman and Conover(1979) showed the fact that the rank transformation is a robust and powerful procedure in the linear regression. In this paper, we show that we can also use the rank transformation to nonparametric regression to achieve the robustness.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.575-583
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• 2000

Consider the problem of estimating regression function from a set of data which is contaminated by a long-tailed error distribution. The linear smoother is a kind of a local weighted average of response, so it is not robust against outliers. The kernel M-smoother and the lowess attain robustness against outliers by down-weighting outliers. However, the kernel M-smoother and the lowess requires the iteration for computing the robustness weights, and as Wang and Scott(1994) pointed out, the requirement of iteration is not a desirable property. In this article, we propose the robust nonparametic regression method which does not require the iteration. Robustness can be achieved not only by down-weighting outliers but also by transforming outliers. The rank transformation is a simple procedure where the data are replaced by their corresponding ranks. Iman and Conover(1979) showed the fact that the rank transformation is a robust and powerful procedure in the linear regression. In this paper, we show that we can also use the rank transformation to nonparametric regression to achieve the robustness.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.26-29
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• 2001

In a target tracking problem the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In most nonlinear situations an Extended Robust Kalman Filter(ERKF) can yield acceptable performance as long as the noises are white Gaussian. However, an Extended Robust $H_{\infty}$ Filter (ERHF) can yield acceptable performance when the noises are Laplacian. In this paper, we use the Interacting Multiple Model(IMM) estimator for the problem of target tracking with glint noise. In the IMM method, two filters(ERKF and ERHF) are used in parallel to estimate the state. Computer simulations of a real target tracking shows that hybrid filter used the IMM algorithm has superior performance than a single type filter.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.246-249
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• 2009

Due to the additive white Gaussian noise (AWGN), images are often corrupted. In recent days, Bayesian estimation techniques to recover noisy images in the wavelet domain have been studied. The probability density function (PDF) of an image in wavelet domain can be described using highly-sharp head and long-tailed shapes. If a priori probability density function having the above properties would be applied well adaptively, better results could be obtained. There were some frequently proposed PDFs such as Gaussian, Laplace distributions, and so on. These functions model the wavelet coefficients satisfactorily and have its own of characteristics. In this paper, mixture distributions of Gaussian and Laplace distribution are proposed, which attempt to corporate these distributions' merits. Such mixture model will be used to remove the noise in images by adopting Maximum a Posteriori (MAP) estimation method. With respect to visual quality, numerical performance and computational complexity, the proposed technique gained better results.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.759-766
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• 2013

The paper examines several classes of probability distributions with heavy tails. An (asymptotic) expression for tail probability needs to be known to understand which class a given probability distribution belongs to. It is usually not easy to get expressions for tail probabilities since most absolutely continuous probability distributions are specified by probability density functions and not by distribution functions. The paper proposes a method to obtain asymptotic expressions for tail probabilities using only probability density functions. Some examples are given to illustrate the proposed method.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.575-586
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• 2011

In this paper, we study an asymptotic behavior of the finite-time ruin probability of the compound Poisson model in the case that the initial surplus is large. To compare an exact ruin probability with an approximate one, we place the focus on the exact calculation for the ruin probability when the claim size distribution is regularly varying tailed (i.e. exponential claims and inverse Gaussian claims). We estimate an adjustment coefficient in these examples and show the relationship between the adjustment coefficient and the safety premium. The illustration study shows that as the safety premium increases so does the adjustment coefficient. Larger safety premium means lower "long-term risk", which only stands to reason since higher safety premium means a faster rate of safety premium income to offset claims.

• Molecules and Cells
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• v.26 no.3
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• pp.314-318
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• 2008

Korean long-tailed goral (Nemorhaedus caudatus) is one of the most endangered species in South Korea. However, detailed species distribution and sex ratio data on the elusive goral are still lacking due to difficulty of identification of the species and sex in the field. The primary aim of this study was to develop an economical PCR-RFLP method to identify species using invasive or non-invasive samples from five Korean ungulates: goral (N. caudatus), roe deer (Capreolus pygargus), feral goat (Capra hircus), water deer (Hydropotes inermis) and musk deer (Moschus moschiferus). The secondary aim was to find more efficient molecular sexing techniques that may be applied to invasive or non-invasive samples of ungulate species. We successfully utilized PCR-RFLP of partial mitochondrial cytochrome b gene (376 bp) for species identification, and sex-specific amplification of ZFX/Y and AMELX/Y genes for sexing. Three species (goral, goat and water deer) showed distinctive band patterns by using three restriction enzymes (Xbal, Stul or Sspl). Three different sexing primer sets (LGL331/335 for ZFX/Y gene; SE47/48 or SE47/53 for AMELX/Y gene) produced sex-specific band patterns in goral, goat and roe deer. Our results suggest that the molecular analyses of non-invasive samples might provide us with potential tools for the further genetic and ecological study of Korean goral and related species.

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.1
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• pp.31-38
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• 2005

This paper is focused on the research of environmental and human factors for a design of PMVbased air conditioning system in the ship. In the results from environmental factor research, it is possible to dissatisfy thermally in the wheel house and communication room of 25 ton and engine room of 100 ton. The clothing and activity in the ship is modified using inland indoor characteristics. Thermal resistance of clothing may be more sensitive to PMV(predicted mean vote) than metabolic rate because of large deviation among maritime polices. The distribution of human factor is right long-tailed than standard normal distribution.