• Title/Summary/Keyword: truncated geometric distribution

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A Characterization of Negative Binomial Distribution Truncated at Zero

  • Shanmugam, R.
    • Journal of the Korean Statistical Society
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    • v.11 no.2
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    • pp.131-138
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    • 1982
  • Analogous to Singh's (1978) characterization of positive-Poisson distributioin and Shanmugam and Singh's (1992) characterization of logarithmic series distribution, a characterization and its statistical application of the negative binomial distribution truncated at zero are given in this paper. While it is known that under certain conditions the negative binomial distribution truncted at zero approaches the positive-Poisson and the logarithmic series distributions, we show here that the results of this paper approach in limit the results of Singh, and Shanmugam and Singh, respectively. Using the biologicla data from Sampford (1955), we illusrate our results. Also, expressions are explicitly given to test the hypothesis whether a random sample is indeed from a geometric distribution.

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A Test for Randomness of the Binary Random Sequence (이진확률수열의 무작위성 검정)

  • Yeo, In-Kwon
    • The Korean Journal of Applied Statistics
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    • v.27 no.1
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    • pp.115-122
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    • 2014
  • A test for randomness of the binary random sequence is proposed in this paper. The proposed test statistic is based on the mean length of runs distributed with truncated geometric distribution and asymptotically ${\chi}^2_2$-distributed when the size of the sequences is large. A small Monte Carlo simulation compared the size of the test with a significant level as well as evaluated the test power. We applied the proposed method to the sequence of yes or no numbers in Lotto 6/45 and concluded that the randomness of Lotto is retained.

Buckling analysis of functionally graded truncated conical shells under external displacement-dependent pressure

  • Khayat, Majid;Poorveis, Davood;Moradi, Shapour
    • Steel and Composite Structures
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    • v.23 no.1
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    • pp.1-16
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    • 2017
  • This paper is presented to solve the buckling problem of functionally graded truncated conical shells subjected to displacement-dependent pressure which remains normal to the shell middle surface throughout the deformation process by the semi-analytical finite strip method. Material properties are assumed to be temperature dependent, and varied continuously in the thickness direction according to a simple power law distribution in terms of the volume fraction of a ceramic and metal. The governing equations are derived based on first-order shear deformation theory which accounts for through thickness shear flexibility with Sanders-type of kinematic nonlinearity. The element linear and geometric stiffness matrices are obtained using virtual work expression for functionally graded materials. The load stiffness also called pressure stiffness matrix which accounts for variation of load direction is derived for each strip and after assembling, global load stiffness matrix of the shell which may be un-symmetric is formed. The un-symmetric parts which are due to load non-uniformity and unconstrained boundaries have been separated. A detailed parametric study is carried out to quantify the effects of power-law index of functional graded material and shell geometry variations on the difference between follower and non-follower lateral buckling pressures. The results indicate that considering pressure stiffness which arises from follower action of pressure causes considerable reduction in estimating buckling pressure.

Empirical Bayes Estimation of the Probability of Discovering a New Species (신종발견확률의 경험적 베이지안 추정에 관한 연구)

  • Joo Ho Lee
    • The Korean Journal of Applied Statistics
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    • v.7 no.1
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    • pp.159-172
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    • 1994
  • An empirical Bayes estimator of the probability of discovering a new species is proposed when some prior information is available on the number f species. The new estimator is shown via simulations to have only a moderate bias and a smaller RMSE than Good's estimator when the species population follows a truncated geometric distribution.

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Randomizing Sequences of Finite Length (유한 순서열의 임의화)

  • Huh, Myung-Hoe;Lee, Yong-Goo
    • The Korean Journal of Applied Statistics
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    • v.23 no.1
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    • pp.189-196
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    • 2010
  • It is never an easy task to physically randomize the sequence of cards. For instance, US 1970 draft lottery resulted in a social turmoil since the outcome sequence of 366 birthday numbers showed a significant relationship with the input order (Wikipedia, "Draft Lottery 1969", Retrieved 2009/05/01). We are motivated by Laplace's 1825 book titled Philosophical Essay on Probabilities that says "Suppose that the numbers 1, 2, ..., 100 are placed, according to their natural ordering, in an urn, and suppose further that, after having shaken the urn, to shuffle the numbers, one draws one number. It is clear that if the shuffling has been properly done, each number will have the same chance of being drawn. But if we fear that there are small differences between them depending on the order in which the numbers were put into the urn, we can decrease these differences considerably by placing these numbers in a second urn in the order in which they are drawn from the first urn, and then shaking the second urn to shuffle the numbers. These differences, already imperceptible in the second urn, would be diminished more and more by using a third urn, a fourth urn, &c." (translated by Andrew 1. Dale, 1995, Springer. pp. 35-36). Laplace foresaw what would happen to us in 150 years later, and, even more, suggested the possible tool to handle the problem. But he did omit the detailed arguments for the solution. Thus we would like to write the supplement in modern terms for Laplace in this research note. We formulate the problem with a lottery box model, to which Markov chain theory can be applied. By applying Markov chains repeatedly, one expects the uniform distribution on k states as stationary distribution. Additionally, we show that the probability of even-number of successes in binomial distribution with trials and the success probability $\theta$ approaches to 0.5, as n increases to infinity. Our theory is illustrated to the cases of truncated geometric distribution and the US 1970 draft lottery.