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A generalization of the binomial distribution [PDF]
Communications in Statistics - Theory and Methods, 1995 This paper presents a new departure in the generalization of the binomial distribution by adopting the assumption that the underlying Bernoulli trials take on the values α or β where α < β, rather than the conventional values 0 or 1. The adoption of this more general assumption renders the binomial distribution a four-parameter distribution of the form
James C. Fu, Robert Sproule
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THE TRUNCATED NEGATIVE BINOMIAL DISTRIBUTION [PDF]
Biometrika, 1955 (1920), Fisher (1941), Haldane (1941), Anscoinbe (1950) and Bliss & Fisher (1953), and is extensively used for the description of data too heterogeneous to be fitted by a Poisson distribution. Observed samples, however, may be truncated, in the sense that the number of individuals falling into the zero class cannot be determined.
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On a property of the binomial distribution
Trabajos de estadistica y de investigacion operativa, 1967In this paper we establish a property of the binomial distribution This property refers to the conditional distribution ofY forX=x in the bivariate discrete distribution of (X, Y). It has been shown that when this conditional distribution is the convolution of a random variableX1 with the random variableX2, then the form of the joint distribution is ...
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Generalized Negative Binomial Distributions [PDF]
Journal of Statistical Physics, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Application of the binomial distribution
1983Some of the general concepts and properties of distributions were introduced in Chapter 2. A number of standard distributions such as binomial, Poisson, normal, lognormal, exponential, gamma, Weibull, Rayleigh were also mentioned. Most of these distributions and their application in reliability evaluation are discussed in Chapter 6.
Roy Billinton, Ronald N. Allan
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Binomial approximation to the Poisson binomial distribution
Statistics & Probability Letters, 1991Abstract Upper and lower bounds are given for the total variation distance between the distribution of a sum S of n independent, non-identically distributed 0–1 random variables and the binomial distribution B ( n, p ) having the same expectation as S . The proof uses the Stein—Chen technique.
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An Approximation to Binomial Distribution
Journal of Statistical Theory and Practice, 2014There are some methods for approximating binomial distribution used under appropriate conditions. This article provides a continuous approximation function for this distribution, which will be obtained by solving a differential equation. Then the parameters of achieved density function are estimated by method of moments.
Hossein Bevrani, S. Sharifi Far
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1999
The binomial distribution is the probability distribution of compound events (section 3.6) consisting of the joint occurrence of independent simple events (sections 3.9 and 15.3). Each simple event may take two complementary forms (section 3.7) of which the probabilities are p and q respectively.
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The binomial distribution is the probability distribution of compound events (section 3.6) consisting of the joint occurrence of independent simple events (sections 3.9 and 15.3). Each simple event may take two complementary forms (section 3.7) of which the probabilities are p and q respectively.
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On the limit of the Markov binomial distribution
Journal of Applied Probability, 1981Let X 1 X 2, · ·· be a Markov Bernoulli sequence with initial probabilities p of success and q = 1 – p of failure, and probabilities 1 – (1 – π) p, (1 – π) p in the first row and (1 – π) (1 – p), (1 – π) p + πin the second row of the transition matrix. If we define Sn = Σ i=
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1966
The binomial distribution is the most important of the non-normal distributions. Its most widely used application is estimating the ‘fraction defective’ in industry (the fraction defective is the proportion of articles which fail to meet a given standard, e.g.
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The binomial distribution is the most important of the non-normal distributions. Its most widely used application is estimating the ‘fraction defective’ in industry (the fraction defective is the proportion of articles which fail to meet a given standard, e.g.
openaire +2 more sources