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In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the ...
The quantile function, Q, of a probability distribution is the inverse of its cumulative distribution function F. The derivative of the quantile function, namely the quantile density function, is yet another way of prescribing a probability distribution. It is the reciprocal of the pdf composed with the quantile function.
The multivariate normal distribution is said to be "non-degenerate" when the symmetric covariance matrix is positive definite. In this case the distribution has density [ 5 ] where is a real k -dimensional column vector and is the determinant of , also known as the generalized variance.
In statistics, the Q-function is the tail distribution function of the standard normal distribution. [ 1 ][ 2 ] In other words, is the probability that a normal (Gaussian) random variable will obtain a value larger than standard deviations. Equivalently, is the probability that a standard normal random variable takes a value larger than .
In probability theory and statistics, the cumulantsκn of a probability distribution are a set of quantities that provide an alternative to the moments of the distribution. Any two probability distributions whose moments are identical will have identical cumulants as well, and vice versa. The first cumulant is the mean, the second cumulant is ...
In mathematics, a function from a set X to a set Y assigns to each element of X exactly one element of Y. [ 1 ] The set X is called the domain of the function [ 2 ] and the set Y is called the codomain of the function. [ 3 ] Functions were originally the idealization of how a varying quantity depends on another quantity.
The cumulative distribution function of a real-valued random variable is the function given by [ 2 ]: p. 77. (Eq.1) where the right-hand side represents the probability that the random variable takes on a value less than or equal to . The probability that lies in the semi-closed interval , where , is therefore [ 2 ]: p. 84. (Eq.2) In the ...
In Analytica release 4.4, the Smoothing option for PDF results uses KDE, and from expressions it is available via the built-in Pdf function. In C/C++, FIGTree is a library that can be used to compute kernel density estimates using normal kernels. MATLAB interface available. In C++, libagf is a library for variable kernel density estimation.