Results 281 to 290 of about 341,037 (316)
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Some Truncated Bivariate Distributions
Acta Applicandae Mathematicae, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nadarajah, Saralees, Kotz, Samuel
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Bivariate inverse gaussian distribution
Annals of the Institute of Statistical Mathematics, 1981A bivariate inverse Gaussian (IG) density function is constructed. Relations of the bivariate IG distribution to the normal and χ2 distributions are established. The corresponding bivariate random walk (RW) density function is obtained. The properties and behaviour of bivariate IG distribution are studied for large parametric values.
Al-Hussaini, Essam K. +1 more
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Statistics & Probability Letters, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Olkin, Ingram, Liu, Ruixue
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Olkin, Ingram, Liu, Ruixue
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Continuous Bivariate Distributions, Emphasising Applications.
Journal of the American Statistical Association, 1991Continuous Bivariate Distributions, Emphasizing Applications. By T. P. Hutchinson and C. D. Lai. ISBN 0 7316 7206 2. Rumsby, Adelaide, 1990. xxxii + 412 pp. £38.
William I. Notz +2 more
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Bivariate Continuous Distribution
1979Bivariate continuous distributions are defined in Section 1, and change of variables problems are considered in Section 2. In Section 3, we prove some results which will be needed in deriving statistical methods for analyzing normally distributed measurements.
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Bivariate Teissier Distributions
2017We first give historical remarks about the forgotten univariate Teissier model. We introduce symmetric and asymmetric bivarite versions of the Teissier distribution and outline basic properties. The corresponding copula is obtained and applications are discussed.
Nikolai Kolev, Ngo Ngoc, Yang Ting Ju
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Bivariate Hofmann distributions
Journal of Applied Statistics, 2003The aim of this paper is to develop some bivariate generalizations of the Hofmann distribution. The Hofmann distribution is known to give nice fits for overdispersed data sets. Two bivariate models are proposed. Recursive formulae are given for the evaluation of the probability function. Moments, conditional distributions and marginal distributions are
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2009
In introductory statistics courses, one has to know why the (univariate) normal distribution is important—especially that the random variables that occur in many situations are approximately normally distributed and that it arises in theoretical work as an approximation to the distribution of many statistics, such as averages of independent random ...
N. Balakrishna, Chin Diew Lai
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In introductory statistics courses, one has to know why the (univariate) normal distribution is important—especially that the random variables that occur in many situations are approximately normally distributed and that it arises in theoretical work as an approximation to the distribution of many statistics, such as averages of independent random ...
N. Balakrishna, Chin Diew Lai
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Bivariate Exponential Distributions
Journal of the American Statistical Association, 1960Abstract A bivariate distribution is not determined by the knowledge of the margins. Two bivariate distributions with exponential margins are analyzed and another is briefly mentioned. In the first distribution (2.1) the conditional expectation of one variable decreases to zero with increasing values of the other one.
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