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The results of this work have been generalized by Bharucha-Reid [1, 7] on a general probability measure space.
Let P be a general probability distribution on ( Ω, F ).
This paper presents a new mixed integer nonlinear stochastic staff scheduling model, where the workforce demands are under uncertainty, with a general probability distribution.
The algorithms are stated in terms of operations on a general probability density function representing a single feature of the environment.
The CM is described locally by a general Probability Density Function (PDF), which is approximated by a truncated spectral expansion with a number of 'components' much smaller than the number of chemical components in the original mixture.
We have proposed, under a general probability sampling design, a two-phase sampling procedure, when the size of a domain (small area) is not known, for estimating the domain total, the first phase being exclusively devoted to arriving at a good estimator of the size of the domain and the second phase being designed to deal with the domain estimation.
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Let f follow a gamma distribution such that The gamma distribution is a very general probability density allowing for shapes ranging from an exponential (when β = 1) through to normal-like distributions depending upon the values of α and β.
Jeffrey's model can be generalised by introducing a more general probability updating rule (e.g., Jeffrey conditionalisation).
Further, generally speaking, it is difficult to give a uniform or general Probability Density Function (PDF) or Cumulative Distribution Function (CDF) of the inter-vehicle distances or connection duration length under different application scenarios such as overtaking, platoon and collisions.
A solution of this general probability estimation problem is obtained by treating it as a nonparametric regression problem.
Off course patients can have several risk factors, in this case the system will reason over the different probabilities to determine the general probability that a patient belongs to a risk group.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com