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IT
GAUSSIAN PROCESS
It's a stochastic process (Xt) with t ? R+, where random variables constituting the random vector n-dimensional (Xt1, Xt2, Xt3, …, Xtn) for ?n ? N, versus time (t1, t2, t3, …, tn) per ?n ? R+, are distributed as a multivariate Gaussian distribution, according to the following equation for the probability density:
Where b represents the expected value of the random variable function versus time and K the covariance between the random variables.
Note that this process is uniquely determined by assigning the functions:
where K is a symmetric function and semi positive definite.
Editor: Giuliano DI TOMMASO
