Multidimensional Time Model for Probability Cumulative Function
*Michael Fundator, Sackler Colloquium of the National Academy of Sciences
Keywords: decision problem, procedure, complete class, dimension, finite-dimensional time model, normally distributed, random variable, processes of Brownian motion, Edgeworth’s form, Gram-Charlier Type A series, Chebyshev-Hermite polynomials,
How does cumulative distribution function change in relation to time change in sampling patterns? Multidimensional time model for probability cumulative function can be reduced to finite-dimensional time model with two ordinal numbers: 4 for the summation and multiplication over events and their probabilities and 17 for the fractal-dimensional time arising from alike supersymmetrical properties of probability. It is greatly applicable to DNA analysis.