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The French mathematician Siméon-Denis Poisson developed his function in 1830 to describe the number of times a gambler would win a rarely won game of chance in a large number of tries.
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The SaTScan Poisson parser, developed specifically for CASE, raises an alert if a detected cluster ends within the last week.
We modeled the probability of generating contigs from sequences which overlap by chance using an implementation of the Poisson distribution developed by Lander and Waterman [ 20].
Finally, a discrete-event simulation model based on Poisson statistics is developed for the performance measures evaluation.
An approximate analysis based on Poisson statistics is developed in order to explore the performance measures optimization.
However, the Poisson statistical method developed by Beebe et al. could be used to determine the unbinding force required to separate a single pair of antigen and antibody molecules [29 31].
By treating the mechanical unfolding of polyproteins as the superposition of multiple identical Poisson processes, we developed a simple stochastic analysis approach to analyze the dwell time distribution of individual unfolding events in polyprotein unfolding trajectories.
A new finite element Poisson solver is developed and applied to a global gyrokinetic toroidal code (GTC) which employs the field aligned mesh and thus a logically non-rectangular grid in a general geometry.
Motivated by the Type I I multivariate zero-truncated Poisson (ZTP) distribution developed recently by Tian et al. (2014), we in this paper propose a new multivariate zero-truncated Charlier series (ZTCS) distribution, whose limiting form reduces to the Type I I multivariate ZTP distribution.
Because the dependent variable in the regression is a nonnegative count variable with no theoretical upper bound it takes on integer values greater than or equal to zero the most appropriate econometric model for the analysis conducted in this paper is the fixed effects (FE) Poisson regression model developed by Hausman, Hall, and Griliches (Hausman et al. 1984).
Considering the adhesion force measured by AFM was not that of a single antigen-antibody pair, but rather a collective result of interaction forces from multiple antigen/antibody pairs, the Poisson statistical method developed by Beebe et al. [27, 28] could be used to determine the unbinding force required to separate a single pair of antigen and antibody molecules.
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