The crucial job of the theory of classical probability is to
compute and assess probabilities. A deterministic expression of probability
theory will be achieved by the addition of new dimensions to the stochastic
experiments. This is the original and novel idea at the foundation of my
paradigm. As a matter of fact, since the events' outcomes are due to randomness
and chance, then the theory of probability is a nondeterministic system in its
essence. A deterministic experiment and hence a stochastic event will have a
certain result in the complex probability set C after encompassing novel
imaginary dimensions to the chaotic experiment occurring in the real set R.
Thus, we will be fully knowledgeable to predict the outcome of stochastic
experiments that arise in the real world in all stochastic processes if the
random event becomes completely predictable. Hence, extending the real
probabilities set R to the deterministic complex probabilities set C = R + M by
including the contributions of the set M which is the imaginary set of
probabilities, is the work that has been accomplished here. Therefore, a novel
paradigm of stochastic sciences and prognostic was laid down in which all
stochastic phenomena in R were expressed deterministically in C since this
extension was found to be successful. I coined this original model with the
term: “The Complex Probability Paradigm” or CPP for short. Knowing that it was
illustrated and initiated in my previous research publications. Henceforth,
this original probability paradigm will be applied in this work to Regular
Markov Chains and Processes.
Author(s) Details
Abdo Abou Jaoudé
Department of Mathematics and Statistics, Faculty of Natural and Applied
Sciences, Notre Dame University-Louaizé, Lebanon.
Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48006-18-9/CH3
No comments:
Post a Comment