Results 281 to 290 of about 577,267 (335)

A Bayesian mixture model for Poisson network autoregression. [PDF]

Soc Netw Anal Min
Hung E, Mantziou A, Reinert G.
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A Geospatial Analysis of the Sleep Surgeon Workforce in the United States. [PDF]

Laryngoscope Investig Otolaryngol
Saroya J, Singh A, Chang JL, Durr ML.
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Improved prediction and flagging of extreme random effects for non-Gaussian outcomes using weighted methods. [PDF]

Biometrics
Neuhaus J, McCulloch C, Boylan R.
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Paired count regressions for modeling the number of doctor consultations and non-prescribed drugs intake. [PDF]

Stat Methods Med Res
Gonçalves JN, Barreto-Souza W, Ombao H.
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Alternative methods for analyzing cross-sectional studies of common outcomes: A guide for healthcare professionals. [PDF]

J Taibah Univ Med Sci
Aljawadi MH.
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On a characterization of Poisson distribution

Journal of Applied Probability, 1970
Recently Rao (1963) has considered discrete models where an original observation produced by nature is subjected to a destructive process and we observe the undestroyed part of the original observation. Suppose the original observation produced by nature is distributed according to a Poisson distribution with parameter λ and the probability that the ...
A. B. L. Srivastava, R. C. Srivastava
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Poisson and Normal Distributions [PDF]

, 1974
The Poisson distribution is of great importance in theory and in practice. It has the added virtue of being a simple mathematical object. We could have introduced it at an earlier stage in the book, and the reader was alerted to this in §4.4. However, the belated entrance will give it more prominence, as well as a more thorough discussion than would be
Kai Lai Chung, Farid AitSahlia
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Poisson on the poisson distribution

Statistics & Probability Letters, 1982
Abstract A translation of the totality of Poisson's own 1837 discussion of the Poisson distribution is presented, and its relation to earlier work of De Moivre is briefly noted.
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On a characterization of Poisson distributions

Journal of Applied Probability, 1972
The conjecture pronounced at the end of the paper of Srivastava and Srivastava (1970) is proved in this paper. It gives the following characterization of (bivariate) Poisson distributions. Suppose that items of two types have been observed certain numbers of times, but these original observations have been reduced due to a destructive process which is ...
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The Poisson Pascal Distribution

Biometrics, 1961
Elementary distributions such as the Poisson, the Logarithmic and the Binomial which can be formulated on the basis of simple models have been found to be inadequate to describe the situations which occur in a number of phenomena. The Neyman Type A (cf. Evans [5]), the Negative Binomial (cf. Bliss and Fisher [3]), and the Poisson Binomial (cf.
S. K. Katti, John Gurland
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