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Random variate. In probability and statistics, a random variate or simply variate is a particular outcome or realization of a random variable; the random variates which are other outcomes of the same random variable might have different values (random numbers). A random deviate or simply deviate is the difference of a random variate with ...
In mathematics, a codomain or set of destination of a function is a set into which all of the output of the function is constrained to fall. It is the set Y in the notation f: X → Y. The term range is sometimes ambiguously used to refer to either the codomain or the image of a function. A codomain is part of a function f if f is defined as a ...
The order in probability notation is used in probability theory and statistical theory in direct parallel to the big-O notation that is standard in mathematics.Where the big-O notation deals with the convergence of sequences or sets of ordinary numbers, the order in probability notation deals with convergence of sets of random variables, where convergence is in the sense of convergence in ...
correlation. so that. where E is the expected value operator. Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X, we have the covariance of a variable with itself (i.e. ), which is called the variance and is more commonly denoted as ...
A weight function is a mathematical device used when performing a sum, integral, or average to give some elements more "weight" or influence on the result than other elements in the same set. The result of this application of a weight function is a weighted sum or weighted average. Weight functions occur frequently in statistics and analysis ...
A more familiar principal branch function, limited to real numbers, is that of a positive real number raised to the power of 1/2. For example, take the relation y = x 1/2, where x is any positive real number. This relation can be satisfied by any value of y equal to a square root of x (either positive or negative).
Counting measure. In mathematics, specifically measure theory, the counting measure is an intuitive way to put a measure on any set – the "size" of a subset is taken to be the number of elements in the subset if the subset has finitely many elements, and infinity if the subset is infinite. [1]
In the case m 0 = 1, this is equivalent to the existence of a random variable X supported on [0, 1], such that E[X n] = m n. The essential difference between this and other well-known moment problems is that this is on a bounded interval , whereas in the Stieltjes moment problem one considers a half-line [0, ∞) , and in the Hamburger moment ...
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