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Suppose further that the stochastic vector r is jointly normally distributed.
Stochastic vector redirects here.
That is, a stochastic vector uniquely identifies a point on the face opposite of the orthogonal corner of the standard simplex.
In mathematics and statistics, a probability vector or stochastic vector is a vector with non-negative entries that add up to one.
Thus, each row of a right stochastic matrix (or column of a left stochastic matrix) is a stochastic vector.
In the same vein, one may define stochastic vector (also called probability vector) as a vector whose elements are nonnegative real numbers which sum to 1.
These two requirements show that stochastic vectors have a geometric interpretation: A stochastic vector is a point on the "far face" of a standard orthogonal simplex.
The probabilistic automaton may be defined as an extension of a non-deterministic finite automaton , together with two probabilities: the probability of a particular state transition taking place, and with the initial state replaced by a stochastic vector giving the probability of the automaton being in a given initial state.
In particular, the state of a probabilistic automaton is always a stochastic vector, since the product of any two stochastic matrices is a stochastic matrix, and the product of a stochastic vector and a stochastic matrix is again a stochastic vector.