• Title/Summary/Keyword: Random distribution function

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Reliability in Two Independent Uniform and Power Function-Half Normal Distribution

  • Woo, Jung-Soo
    • Communications for Statistical Applications and Methods
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    • v.15 no.3
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    • pp.325-332
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    • 2008
  • We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

ROC Curve for Multivariate Random Variables

  • Hong, Chong Sun
    • Communications for Statistical Applications and Methods
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    • v.20 no.3
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    • pp.169-174
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    • 2013
  • The ROC curve is drawn with two conditional cumulative distribution functions (or survival functions) of the univariate random variable. In this work, we consider joint cumulative distribution functions of k random variables, and suggest a ROC curve for multivariate random variables. With regard to the values on the line, which passes through two mean vectors of dichotomous states, a joint cumulative distribution function can be regarded as a function of the univariate variable. After this function is modified to satisfy the properties of the cumulative distribution function, a ROC curve might be derived; moreover, some illustrative examples are demonstrated.

ON THE PRODUCT OF t AND BESSEL RANDOM VARIABLES

  • NADARAJAH SARALEES
    • Communications of the Korean Mathematical Society
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    • v.20 no.3
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    • pp.547-562
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    • 2005
  • The distribution of products of random variables is of interest in many areas of the sciences, engineering and medicine. This has increased the need to have available the widest possible range of statistical results on products of random variables. In this note, the distribution of the product | XY | is derived when X and Y are Student's t and Bessel function random variables distributed independently of each other.

Role of Distribution Function in Vibration Related Error of Strapdown INS in Random Vibration Test

  • Abdoli, A.;Taghavi, S.H.
    • International Journal of Aeronautical and Space Sciences
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    • v.15 no.3
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    • pp.302-308
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    • 2014
  • In this paper, a detailed investigation of the random vibration test is presented for strapdown inertial navigation systems (INS). The effect of the random vibration test has been studied from the point of view of navigation performance. The role of distribution functions and RMS value is represented to determine a feasible method to reject or reduce vibration related error in position and velocity estimation in inertial navigation. According to a survey conducted by the authors, this is the first time that the effect of the distribution function in vibration related error has been investigated in random vibration testing of INS. Recorded data of navigation grade INS is used in offline static navigation to examine the effect of different characteristics of random vibration tests on navigation error.

DECOMPOSITION OF THE RANDOM VARIABLE WHOSE DISTRIBUTION IS THE RIESZ-NÁGY-TAKÁCS DISTRIBUTION

  • Baek, In Soo
    • Journal of the Chungcheong Mathematical Society
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    • v.26 no.2
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    • pp.421-426
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    • 2013
  • We give a series of discrete random variables which converges to a random variable whose distribution function is the Riesz-N$\acute{a}$gy-Tak$\acute{a}$cs (RNT) distribution. We show this using the correspondence theorem that if the moments coincide then their corresponding distribution functions also coincide.

Reliability-based stochastic finite element using the explicit probability density function

  • Rezan Chobdarian;Azad Yazdani;Hooshang Dabbagh;Mohammad-Rashid Salimi
    • Structural Engineering and Mechanics
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    • v.86 no.3
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    • pp.349-359
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    • 2023
  • This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

On the Comparison of Particle Swarm Optimization Algorithm Performance using Beta Probability Distribution (베타 확률분포를 이용한 입자 떼 최적화 알고리즘의 성능 비교)

  • Lee, ByungSeok;Lee, Joon Hwa;Heo, Moon-Beom
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.8
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    • pp.854-867
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    • 2014
  • This paper deals with the performance comparison of a PSO algorithm inspired in the process of simulating the behavior pattern of the organisms. The PSO algorithm finds the optimal solution (fitness value) of the objective function based on a stochastic process. Generally, the stochastic process, a random function, is used with the expression related to the velocity included in the PSO algorithm. In this case, the random function of the normal distribution (Gaussian) or uniform distribution are mainly used as the random function in a PSO algorithm. However, in this paper, because the probability distribution which is various with 2 shape parameters can be expressed, the performance comparison of a PSO algorithm using the beta probability distribution function, that is a random function which has a high degree of freedom, is introduced. For performance comparison, 3 functions (Rastrigin, Rosenbrock, Schwefel) were selected among the benchmark Set. And the convergence property was compared and analyzed using PSO-FIW to find the optimal solution.

A Random Shock Model for a Linearly Deteriorating System

  • Lee, Ji-Yeon;Lee, Eui-Young
    • Journal of the Korean Statistical Society
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    • v.24 no.2
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    • pp.471-479
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    • 1995
  • A random shock model for a linearly deteriorating system is introduced. The system deteriorating linearly with time is subject to random shocks which arrive according to a Poisson process and decrease the state of the system by a random amount. The system is repaired by a repairmen arriving according to another Poisson process if the state when he arrives is below a threshold. Explicit expressions are deduced for the characteristic function of the distribution function of X(t), the state of the system at time t, and for the distribution function of X(t) if X(t) is over the threshold. The stationary case is briefly discussed.

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ESTIMATION OF THE DISTRIBUTION FUNCTION FOR STATIONARY RANDOM FIELDS OF ASSOCIATED PROCESSES

  • Kim, Tae-Sung;Ko, Mi-Hwa;Yoo, Yeon-Sun
    • Communications of the Korean Mathematical Society
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    • v.19 no.1
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    • pp.169-177
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    • 2004
  • For a stationary field $\{X_{\b{j}},\b{j}{\;}\in{\;}{\mathbb{Z}}^d_{+}\}$ of associated random variables with distribution function $F(x)\;=\;P(X_{\b{1}}\;{\leq}\;x)$ we study strong consistency and asymptotic normality of the empirical distribution function, which is proposed as an estimator for F(x). We also consider strong consistency and asymptotic normality of the empirical survival function by applying these results.

Notes on the Ratio and the Right-Tail Probability in a Log-Laplace Distribution

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1171-1177
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    • 2007
  • We consider estimation of the right-tail probability in a log-Laplace random variable, As we derive the density of ratio of two independent log-Laplace random variables, the k-th moment of the ratio is represented by a special mathematical function. and hence variance of the ratio can be represented by a psi-function.

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