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What (who) is Q-Gaussian process - definition
Q-Gaussian process
q-Gaussian processes are deformations of the usual Gaussian distribution. There are several different versions of this; here we treat a multivariate deformation, also addressed as q-Gaussian process, arising from free probability theory and corresponding to deformations of the canonical commutation relations.
Gaussian process
STOCHASTIC PROCESS SUCH THAT EVERY FINITE COLLECTION OF RANDOM VARIABLES HAS A MULTIVARIATE NORMAL DISTRIBUTION
Gaussian stochastic process; Gaussian processes; Gaussian Process; Gaussian Processes; Applications of Gaussian processes; Bayesian Kernel Ridge Regression
In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that every finite collection of those random variables has a multivariate normal distribution, i.e.
Gaussian binomial coefficient
FAMILY OF POLYNOMIALS
Q-binomial coefficient; Q-binomial; Gaussian coefficient; Gaussian binomial; Q-binomial theorem; Gaussian polynomial; Gaussian polynomials; Gaussian binomial coefficients; Q-binomial coefficients
In mathematics, the Gaussian binomial coefficients (also called Gaussian coefficients, Gaussian polynomials, or q-binomial coefficients) are q-analogs of the binomial coefficients. The Gaussian binomial coefficient, written as \binom nk_q or \begin{bmatrix}n\\ k\end{bmatrix}_q, is a polynomial in q with integer coefficients, whose value when q is set to a prime power counts the number of subspaces of dimension k in a vector space of dimension n over a finite field with q elements.
