probability function
111Realization (probability) — In probability and statistics, a realization, or observed value, of a random variable is the value that is actually observed (what actually happened). The random variable itself should be thought of as the process how the observation comes about …
112Smoothness (probability theory) — In probability theory and statistics, smoothness of a density function is a measure which determines how many times the density function can be differentiated, or equivalently the limiting behavior of distribution’s characteristic function.… …
113Continuous probability distribution — In probability theory, a probability distribution is called continuous if its cumulative distribution function is continuous. That is equivalent to saying that for random variables X with the distribution in question, Pr [ X = a ] = 0 for all… …
114Empirical distribution function — In statistics, an empirical distribution function is a cumulative probability distribution function that concentrates probability 1/ n at each of the n numbers in a sample.Let X 1,ldots,X n be iid random variables in mathbb{R} with the cdf F ( x… …
115Partition function (quantum field theory) — In quantum field theory, we have a generating functional, Z [J] of correlation functions and this value, called the partition function is usually expressed by something like the following functional integral::Z [J] = int mathcal{D}phi e^{i(S… …
116Characteristic function — In mathematics, characteristic function can refer to any of several distinct concepts: The most common and universal usage is as a synonym for indicator function, that is the function which for every subset A of X, has value 1 at points of A and… …
117One-way function — Unsolved problems in computer science Do one way functions exist? In computer science, a one way function is a function that is easy to compute on every input, but hard to invert given the image of a random input. Here easy and hard are to be… …
118Measurable function — In mathematics, particularly in measure theory, measurable functions are structure preserving functions between measurable spaces; as such, they form a natural context for the theory of integration. Specifically, a function between measurable… …
119Hartley function — The Hartley function is a measure of uncertainty, introduced by Ralph Hartley in 1928. If we pick a sample from a finite set A uniformly at random, the information revealed after we know the outcome is given by the Hartley function If the base of …
120Naor-Reingold Pseudorandom Function — In 1997, Moni Naor and Omer Reingold described efficient constructions for various cryptographic primitives in private key as well as public key cryptography. Their result is the construction of an efficient pseudorandom function. Let p and l be… …
