• Title/Summary/Keyword: biased distribution

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MISCLASSIFICATION IN SIZE-BIASED MODIFIED POWER SERIES DISTRIBUTION AND ITS APPLICATIONS

  • Hassan, Anwar;Ahmad, Peer Bilal
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.13 no.1
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    • pp.55-72
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    • 2009
  • A misclassified size-biased modified power series distribution (MSBMPSD) where some of the observations corresponding to x = c + 1 are misclassified as x = c with probability $\alpha$, is defined. We obtain its recurrence relations among the raw moments, the central moments and the factorial moments. Discussion of the effect of the misclassification on the variance is considered. To illustrate the situation under consideration some of its particular cases like the size-biased generalized negative binomial (SBGNB), the size-biased generalized Poisson (SBGP) and sizebiased Borel distributions are included. Finally, an example is presented for the size-biased generalized Poisson distribution to illustrate the results.

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THE LENGTH-BIASED POWERED INVERSE RAYLEIGH DISTRIBUTION WITH APPLICATIONS

  • MUSTAFA, ABDELFATTAH;KHAN, M.I.
    • Journal of applied mathematics & informatics
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    • v.40 no.1_2
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    • pp.1-13
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    • 2022
  • This article introduces a new distribution called length-biased powered inverse Rayleigh distribution. Some of its statistical properties are derived. Maximum likelihood procedure is applied to report the point and interval estimations of all model parameters. The proposed distribution is also applied to two real data sets for illustrative purposes.

New Definition of the Fibrogram and Its Application to Cotton Blending

  • Jeon, Boong-Soo
    • Fibers and Polymers
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    • v.6 no.4
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    • pp.332-335
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    • 2005
  • The fibrogram theory is newly derived from the superposition principle of the conventional staple diagram, in which the left-hand ends of the fibers have to share a common starting point in order for the fiber length distribution to be measured, and the right-hand ends of the fibers form points. It is shown that the fibrogram is the staple diagram of the fiber sample having different random starting points, as well as the double cumulative distribution function of the frequency length function in the length biased sample. Also, the various means, viz. the numerical mean length, numerical mean length in median, length biased mean length, and length biased mean length in median, and the various upper half means, viz. the numerical upper half mean length, numerical upper half mean length in median, length biased upper half mean length, and length biased upper half mean length in median, are discussed in relation to the cotton blending process.

Blind Algorithms using a Random-Symbol Set under Biased Impulsive Noise (바이어스 된 충격성 잡음 하에서 랜덤 심볼 열을 이용한 블라인드 알고리듬)

  • Kim, Namyong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.4
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    • pp.1951-1956
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    • 2013
  • Distribution-matching type algorithms based on a set of symbols generated in random order provide a limited performance under biased impulsive noise since the performance criterion for the algorithms has no variables for biased signal. For the immunity against biased impulsive noise, we propose, in this paper, a modified performance criterion and derived related blind algorithms based on augmented filter structures and the distribution-matching method using a set of random symbols. From the simulation results, the proposed algorithm based on the proposed criterion yielded superior convergence performance undisturbed by the strong biased impulsive noise.

Spatial Distribution of Mobiles in Cellular Communication Network (이동통신망에서의 셀 내 가입자 분포 분석)

  • Jang, Hee-Seon;Lee, Kwang-Hee;Yoon, Sang-Hum
    • IE interfaces
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    • v.12 no.3
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    • pp.401-405
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    • 1999
  • We present a simulation model to generate the spatial distribution of mobiles in cellular communication network. Three types of spatial distributions are considered; biased, random, and ratio-based distributions. This study also points out and corrects the critical errors performed by Das and Morgera(1997) in getting random location of mobiles. By applying a simple path loss model, the effects of our correction on the signal-to-interference(SIR) ratio are discussed. The numerical results indicate that the variation of SIR in the Das's biased distribution is larger than that of other distributions. As compared with the random distribution, the average SIR error of the biased distribution is 91.1%.

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ON SIZE-BIASED POISSON DISTRIBUTION AND ITS USE IN ZERO-TRUNCATED CASES

  • Mir, Khurshid Ahmad
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.12 no.3
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    • pp.153-160
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    • 2008
  • A size-biased Poisson distribution is defined. Its characterization by using a recurrence relation for first order negative moment of the distribution is obtained. Different estimation methods for the parameter of the model are also discussed. R-Software has been used for making a comparison among the three different estimation methods.

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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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Effect of RF Bias on Plasma Parameters and Electron Energy Distribution in RF Biased Inductively Coupled Plasma

  • Lee, Hyo-Chang;Chung, Chin-Wook
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.492-492
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    • 2012
  • RF biased inductively coupled plasma (ICP) has been widely used in various semiconductor etching processes and laboratory plasma researches. However, almost researches for the RF bias have been focused on the controls of dc self-bias voltages, even though the RF bias can change plasma parameters, such as electron temperature, plasma density, electron energy distribution (EED), and their spatial distributions. In this study, we report on the effect of the RF bias on the plasma parameters and the EEDs with various external parameters, such the RF bias power, the ICP power, the gas pressure, the gas mixture, and the frequency of RF bias. Our study shows the correlation between the RF bias and the plasma parameters and gives a crucial key for the understanding of collisionless electron heating mechanism in the RF biased ICP.

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Risk Value Calculation Method for Moderate Risk Concentration Type at Qualitative Risk Analysis Phase (정성적 위험분석 단계에서 중간위험 집중형 위험도 산정 방법)

  • Kim, Seon-Gyoo
    • Korean Journal of Construction Engineering and Management
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    • v.16 no.2
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    • pp.38-45
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    • 2015
  • The risk analysis phase of construction risk management process is subdivided into the qualitative risk analysis that plays a major role, and the quantitative risk analysis acting as a supportive role. The traditional calculation method for quantifying a risk value that has been applied so far is an equation to multiply a probability by an impact simply, but its result shows the low risk value biased distribution. Although another equation that shows the high risk biased distribution as an alternative of traditional method was proposed, both of the low or high risk biased equations do not match with the statistical general knowledge that most natural phenomenons are close to the normal distribution. This study proposes a new risk value calculation method that is concentrated to the moderate risk value. Because the risk value distribution by a new method shows a normal shape similar to natural phenomenon, it helps to choose a middle level not biased to the low or high levels when choosing the level of risk response. Furthermore, it could contribute to improve the flexibility and rationality of risk analysis method by providing additional options for the risk value calculation.

Information Potential and Blind Algorithms Using a Biased Distribution of Random-Order Symbols (랜덤 심볼열의 바이어스된 분포를 이용한 정보 포텐셜과 블라인드 알고리즘)

  • Kim, Namyong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.1
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    • pp.26-32
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    • 2013
  • Blind algorithms based on Information potential of output samples and a set of symbols generated in random order at the receiver go through performance degradation when biased impulsive noise is added to the channel since the cost function composed of information potentials has no variable to deal with biased signal. Aiming at the robustness against biased impulsive noise, we propose, in this paper, a modified information potential, and derived related blind algorithms based on augmented filter structures and a set of random-order symbols. From the simulation results of blind equalization for multipath channels, the blind algorithm based on the proposed information potential produced superior convergence performance in the environments of strong biased impulsive noise.