• Title/Summary/Keyword: inverse Gaussian

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Ruin Probability on Insurance Risk Models (보험위험 확률모형에서의 파산확률)

  • Park, Hyun-Suk;Choi, Jeong-Kyu
    • 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.

Nonlinear rheology of polymer melts: a new perspective on finite chain extensibility effects

  • Wagner Manfred H.
    • Korea-Australia Rheology Journal
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    • v.18 no.4
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    • pp.199-207
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    • 2006
  • Measurements by Luap et al. (2005) of elongational viscosity and birefringence of two nearly monodisperse polystyrene melts with molar masses $M_{w}$ of $206,000g{\cdot}mol^{-1}$ (PS206k) and $465,000g{\cdot}mol^{-1}$ (PS465k) respectively are reconsidered. At higher elongational stresses, the samples showed clearly deviations from the stress optical rule (SOR). The elongational viscosity data of both melts can be modeled quantitatively by the MSF model of Wagner et al. (2005), which is based on the assumption of a strain-dependent tube diameter and the interchain pressure term of Marrucci and Ianniruberto (2004). The only nonlinear parameter of the model, the tube diameter relaxation time, scales with $M_{w}^{2}$. In order to get agreement with the birefringence data, finite chain extensibility effects are taken into account by use of the $Pad\'{e}$ approximation of the inverse Langevin function, and the interchain pressure term is modified accordingly. Due to a selfregulating limitation of chain stretch by the FENE interchain pressure term, the transient elongational viscosity shows a small dependence on finite extensibility only, while the predicted steady-state elongational viscosity is not affected by non-Gaussian effects in agreement with experimental evidence. However, deviations from the SOR are described quantitatively by the MSF model by taking into account finite chain extensibility, and within the experimental window investigated, deviations from the SOR are predicted to be strain rate, temperature, and molar mass independent for the two nearly monodisperse polystyrene melts in good agreement with experimental data.

A Development of Markov Chain Monte Carlo History Matching Technique for Subsurface Characterization (지하 불균질 예측 향상을 위한 마르코프 체인 몬테 카를로 히스토리 매칭 기법 개발)

  • Jeong, Jina;Park, Eungyu
    • Journal of Soil and Groundwater Environment
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    • v.20 no.3
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    • pp.51-64
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    • 2015
  • In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

Note on Stochastic Orders through Length Biased Distributions

  • Choi, Jeen-Kap;Lee, Jin-Woo
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.243-250
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    • 1999
  • We consider $Y=X{\lambda}Z,\;{\lambda}>0$, where X and Z are independent random variables, and Y is the length biased distribution or the equilibrium distribution of X. The purpose of this paper is to consider the distribution of X or Y when the distribution of Z is given and the distribution of Z when the distribution of X or Y is given, In particular, we obtain that the necessary and sufficient conditions for X to be $X^{2}({\upsilon})\;is\;Z{\sim}X^{2}(2)\;and\;for\;Z\;to\;be\;X^{2}(1)\;is\;X{\sim}IG({\mu},\;{\mu}^{2}/{\lambda})$, where $IG({\mu},\;{\mu}^{2}/{\lambda})$ is two-parameter inverse Gaussian distribution. Also we show that X is smaller than Y in the reverse Laplace transform ratio order if and only if $X_{e}$ is smaller than $Y_{e}$ in the Laplace transform ratio order. Finally, we can get the results that if X is smaller than Y in the Laplace transform ratio order, then $Y_{L}$ is smaller than $X_{L}$ in the Laplace transform order, and that if X is smaller than Y in the reverse Laplace transform ratio order, then $_{\mu}X_{L}$ is smaller than $_{\nu}Y_{L}$ in the Laplace transform order.

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Fatigue Damage Model Comparison with Tri-modal Spectrum under Stationary Gaussian Random Processes (정상 정규분포 확률과정의 삼봉형 스펙트럼에 대한 피로손상 모델 비교)

  • Park, Jun-Bum;Jeong, Se-Min
    • Journal of Ocean Engineering and Technology
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    • v.28 no.3
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    • pp.185-192
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    • 2014
  • The riser systems for floating offshore structures are known to experience tri-modal dynamic responses. These are owing to the combined loadings from the low-frequency response due to riser tension behavior, middle-range frequency response coming from winds and waves, and high-frequency response due to vortex induced-vibration. In this study, fatigue damage models were applied to predict the fatigue damages in a well-separated tri-modal spectrum, and the resultant fatigue damages of each model were compared with the most reasonable fatigue damage calculated by the inverse Fourier transform of the spectrum, rain-flow counting method, and Palmgren-Miner rule as a reference. The results show that the fatigue damage models developed for a wide-band spectrum are applicable to the tri-modal spectrum, and both the Benasciutti-Tovo and JB models could most accurately predict the fatigue damages of the tri-modal spectrum responses.

Markov Chain Monte Carlo simulation based Bayesian updating of model parameters and their uncertainties

  • Sengupta, Partha;Chakraborty, Subrata
    • Structural Engineering and Mechanics
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    • v.81 no.1
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    • pp.103-115
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    • 2022
  • The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

Hybrid Watermarking Technique using DWT Subband Structure and Spatial Edge Information (DWT 부대역구조와 공간 윤곽선정보를 이용한 하이브리드 워터마킹 기술)

  • 서영호;김동욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5C
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    • pp.706-715
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    • 2004
  • In this paper, to decide the watermark embedding positions and embed the watermark we use the subband tee structure which is presented in the wavelet domain and the edge information in the spatial domain. The significant frequency region is estimated by the subband searching from the higher frequency subband to the lower frequency subband. LH1 subband which has the higher frequency in tree structure of the wavelet domain is divided into 4${\times}$4 submatrices, and the threshold which is used in the watermark embedding is obtained by the blockmatrix which is consists by the average of 4${\times}$4 submatrices. Also the watermark embedding position, Keymap is generated by the blockmatrix for the energy distribution in the frequency domain and the edge information in the spatial domain. The watermark is embedded into the wavelet coefficients using the Keymap and the random sequence generated by LFSR(Linear feedback shift register). Finally after the inverse wavelet transform the watermark embedded image is obtained. the proposed watermarking algorithm showed PSNR over 2㏈ and had the higher results from 2% to 8% in the comparison with the previous research for the attack such as the JPEG compression and the general image processing just like blurring, sharpening and gaussian noise.

Subpixel Shift Estimation in Noisy Image Using Iterative Phase Correlation of A Selected Local Region (잡음 영상에서 국부 영역의 반복적인 위상 상관도를 이용한 부화소 이동량 추정방법)

  • Ha, Ho-Gun;Jang, In-Su;Ko, Kyung-Woo;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.1
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    • pp.103-119
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    • 2010
  • In this paper, we propose a subpixel shift estimation method using phase correlation with a local region for the registration of noisy images. Phase correlation is commonly used to estimate the subpixel shift between images, which is derived from analyzing shifted and downsampled images. However, when the images are affected by additive white Gaussian noise and aliasing artifacts, the estimation error is increased. Thus, instead of using the whole image, the proposed method uses a specific local region that is less affect by noises. In addition, to improve the estimation accuracy, iterative phase correlation is applied between selected local regions rather than using a fitting function. the restricted range is determined by analyzing the maximum peak and the two adjacent values of the inverse Fourier transform of the normalized cross power spectrum. In the experiments, the proposed method shows higher accuracy in registering noisy images than the other methods. Thus, the edge-sharpness and clearness in the super-resolved image is also improved.

Bayesian ordinal probit semiparametric regression models: KNHANES 2016 data analysis of the relationship between smoking behavior and coffee intake (베이지안 순서형 프로빗 준모수 회귀 모형 : 국민건강영양조사 2016 자료를 통한 흡연양태와 커피섭취 간의 관계 분석)

  • Lee, Dasom;Lee, Eunji;Jo, Seogil;Choi, Taeryeon
    • The Korean Journal of Applied Statistics
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    • v.33 no.1
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    • pp.25-46
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    • 2020
  • This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

Study on Applicability of Frequency Domain-Based Fatigue Analysis for Wide Band Gaussian Process I : Rayleigh PDF (광대역 정규 프로세스에 대한 주파수 영역 기반 피로해석법의 적용성에 관한 연구 I : 레일리 PDF)

  • Choung, Joon-Mo;Kim, Kyung-Su;Nam, Ji-Myung;Koo, Jeong-Bon;Kim, Min-Soo;Shim, Yong-Lae;Urm, Hang-Sub
    • Journal of the Society of Naval Architects of Korea
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    • v.49 no.4
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    • pp.350-358
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    • 2012
  • This paper deals with accuracy of accumulated fatigue damage estimation using stochastic fatigue analysis method based on Rayleigh PDF. From full scale measurement data on an 8100TEU container vessel, zero-order spectral moments for wave- and vibration-induced energy spectral densities are determined on the probability level of 99%. 80 simulation cases in total are prepared according to the variation of ratio of zero-order spectral moments and center frequency of vibration ESD. By using inverse Fourier transformation and rainflow cycle counting for the combined ESD of wave and vibration, exact fatigue damages are derived. Fatigue damages in frequency domain based on Rayleigh PDF show large conservativeness compared to exact fatigue damages in times domain. The main cause of the excessive conservativeness is analyzed by two aspects: ratio of zero crossing and peak frequencies and ratio of initial zero order spectral moments and zero order spectral moments from rainflow stress range distributions. Finally, a guideline of applicability of Rayleigh PDF is proposed for wide band processes.