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The Generalized Discrete Pareto Probability Function [ 18, 19] is used for parameterization of skewed long-tail empirical frequency distributions of our study.
Call P a probability function, and (Ω, F, P) a probability space.
The semantics of propositional probability logic involves a probability function P, satisfying certain properties.
This probability density works much like an ordinary probability function.
A few of them treated the stochastic component, for instance, Li and Yeh (2002) added a random variable into the probability function in ANN-CA model, Wu (2002) combined Monte Carlo approach with probability generalized by statistical method in urban and non-urban simulations.
The result would again be a probability function the uniquely correct prior probability function, according to Weisberg.
The results of this work have been generalized by Bharucha-Reid [1, 7] on a general probability measure space.
In this paper, we have introduced and investigated a new class of generalized functions, called generalized geometrically convex functions.
In this paper, we introduce and study a new class of generalized functions, called generalized geometrically convex functions.
Based on function projective synchronization theorem, a novel type of synchronization scheme called generalized binary function projective synchronization is proposed.
We therefore utilize exceedance probability of a probability distribution function regarding interurban accessibility.
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