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Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted outcome is a vector of correlated random variables rather than a single scalar random variable.
Suppose K is a random variable distributed as the number of successes in n independent Bernoulli trials with probability x of success on each trial; in other words, K has a binomial distribution with parameters n and x.
; Mutual information : Let be a set of random variables.
In probability theory, the Vysochanskij–Petunin inequality gives a lower bound for the probability that a random variable with finite variance lies within a certain number of standard deviations of the variable's mean, or equivalently an upper bound for the probability that it lies further away.
Probability mass function, a function that gives the probability that a discrete random variable is exactly equal to some value
Second moment method, a technique used in probability theory to show that a random variable is positive with positive probability
where denotes the Dirac measure, N is an integer-valued random variable and are random elements of S.
A poisson-distributed random variable is usually used to describe the random number of events occuring over a certain time interval.