• Title/Summary/Keyword: Random Distribution

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On Distribution of Order Statistics from Kumaraswamy Distribution

  • Garg, Mridula
    • Kyungpook Mathematical Journal
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    • v.48 no.3
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    • pp.411-417
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    • 2008
  • In the present paper we derive the distribution of single order statistics, joint distribution of two order statistics and the distribution of product and quotient of two order statistics when the independent random variables are from continuous Kumaraswamy distribution. In particular the distribution of product and quotient of extreme order statistics and consecutive order statistics have also been obtained. The method used is based on Mellin transform and its inverse.

The influence of the random censorship model on the estimation of the scale parameter of the exponential distribution (중도절단모형이 지수분포의 척도모수추정에 미치는 영향)

  • Kim, Namhyun
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.393-402
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    • 2014
  • The simplest and the most important distribution in survival analysis is the exponential distribution. In this paper, we investigate the influence of the random censorship model on the estimation of the scale parameter of the exponential distribution. The considered random censorship models are Koziol-Green model and the generalized exponential distribution model. Two models have different meanings. Through the simulation study, the averages of the estimated values of the parameter do not show big differences, however the MSE of the estimator tends to be bigger when the supposed model is significantly different from the true model.

ANALYSIS OF THE BEHAVIOR OF LIMITING SPECTRAL DENSITY FUNCTION OF LARGE DIMENSIONAL RANDOM MATRICES

  • Choi, Sang-Il
    • Journal of applied mathematics & informatics
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    • v.16 no.1_2
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    • pp.483-488
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    • 2004
  • Results on the analytic behavior of the limiting spectral distribution of large dimensional random matrices, studied in Marcenko and Pastur [2], are derived. Using the Stieltjes transform, it is shown that the limiting distribution has a continuous derivative away from zero, the derivative being analytic whenever it is positive [3]. In the present paper, it is derived that the behavior of it resembles the behavior of a square root function near the boundary of its support.

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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CHARACTERIZATIONS OF THE GAMMA DISTRIBUTION BY INDEPENDENCE PROPERTY OF RANDOM VARIABLES

  • Jin, Hyun-Woo;Lee, Min-Young
    • Journal of the Chungcheong Mathematical Society
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    • v.27 no.2
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    • pp.157-163
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    • 2014
  • Let {$X_i$, $1{\leq}i{\leq}n$} be a sequence of i.i.d. sequence of positive random variables with common absolutely continuous cumulative distribution function F(x) and probability density function f(x) and $E(X^2)$ < ${\infty}$. The random variables X + Y and $\frac{(X-Y)^2}{(X+Y)^2}$ are independent if and only if X and Y have gamma distributions. In addition, the random variables $S_n$ and $\frac{\sum_{i=1}^{m}(X_i)^2}{(S_n)^2}$ with $S_n=\sum_{i=1}^{n}X_i$ are independent for $1{\leq}m$ < n if and only if $X_i$ has gamma distribution for $i=1,{\cdots},n$.

Variance estimation for distribution rate in stratified cluster sampling with missing values

  • Heo, Sunyeong
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.443-449
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    • 2017
  • Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.

Condition of Random Distribution of Residual Dispersion Per Span (RDPS) in Optical Transmission Links with Dispersion Management (분산 제어가 적용된 광전송 링크에서 RDPS의 랜덤 분포 조건)

  • Lee, Seong-Real
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.650-652
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    • 2011
  • Condition of random distribution of residual dispersion per span (RDPS) for transmission of 40 Gbps optical signal with good performance through optical transmission links with dispersion management (DM) of random RDPS distribution and optical phase conjugator (OPC) is induced in this paper.

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The Gauss, Rayleigh and Nakagami Probability Density Distribution Based on the Decreased Exponential Probability Distribution (감쇄지수함수 확률분포에 의한 가우스, 레일레이, 나카가미 확률 밀도 분포)

  • Kim, Jeong-Su;Lee, Moon-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.6
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    • pp.59-68
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    • 2017
  • Random process plays a major role in wireless communication system to analytically derive the probability distribution function of the various statistical distribution. In this paper, we derive the decreasing function of the exponential distribution under the given condition which is expressed as wireless channel condition. The probability distribution function of Gaussian, Laplacian, Rayleigh and Nakagami distribution are also derived. Extensive simulation results of these statistical distributions are provided to prove that random process has a significant role in the wireless communications. In addition, the Rayleigh and Rician channels show specific examples of visible distance communication and invisible distance channel environment. This paper is motivated by that we assume a block fading channel model, where the channel is constant during a transmission block and changes independently between consecutive transmission block, can achieve a better performance in high SNR regime with i.i.d channel. This algorithm for realizing these transforms can be applied to the Kronecker MIMO channel.