In probability theory, the chain rule (also called the general product rule) describes how to calculate the probability of the intersection of, not necessarily...

paradox Chain rule (probability) Class membership probabilities Conditional independence Conditional probability distribution Conditioning (probability) Disintegration...

z}}\right)_{x}\left({\frac {\partial z}{\partial x}}\right)_{y}=-1.} Chain rule (probability): P ( X 1 = x 1 , … , X n = x n ) = ∏ i = 1 n P ( X i = x i ∣ X...

statistics, Markov chain Monte Carlo (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution...

In probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability...

In probability theory, the law (or formula) of total probability is a fundamental rule relating marginal probabilities to conditional probabilities. It...

or Bayes' rule, after Thomas Bayes) gives a mathematical rule for inverting conditional probabilities, allowing one to find the probability of a cause...

Probability is a branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of...

Cromwell's rule, named by statistician Dennis Lindley, states that the use of prior probabilities of 1 ("the event will definitely occur") or 0 ("the event...

addition law of probability, or the sum rule. That is, the probability that an event in A or B will happen is the sum of the probability of an event in...

likelihood via an application of Bayes' rule. From an epistemological perspective, the posterior probability contains everything there is to know about...

Bayesian statistics, Bayes' rule prescribes how to update the prior with new information to obtain the posterior probability distribution, which is the...

Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is an interpretation of the concept of probability, in which, instead of frequency or...

reverse chain rule or change of variables, is a method for evaluating integrals and antiderivatives. It is the counterpart to the chain rule for differentiation...

Probability is a measure of the likeliness that an event will occur. Probability is used to quantify an attitude of mind towards some proposition whose...

In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes...

a predicted value and an observed value, scoring rules assign such a score to a predicted probability distribution and an observed value. On the other...

In probability theory, an event is a subset of outcomes of an experiment (a subset of the sample space) to which a probability is assigned. A single outcome...

field of statistics based on the Bayesian interpretation of probability, where probability expresses a degree of belief in an event. The degree of belief...

\end{aligned}}} . This identity is known as the chain rule of probability. Since these are probabilities, in the two-variable case ∑ i ∑ j P ( X = x i  ...

Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution from which direct...

indifference (also called principle of insufficient reason) is a rule for assigning epistemic probabilities. The principle of indifference states that in the absence...

values, T (for true) and F (for false). The joint probability function is, by the chain rule of probability, Pr ( G , S , R ) = Pr ( G ∣ S , R ) Pr ( S ∣...

The chain rule[citation needed] for Kolmogorov complexity is an analogue of the chain rule for information entropy, which states: H ( X , Y ) = H ( X )...

coefficient or probability that one event is triggered by another event is presented on event chain in the rectangular box. Event chains may trigger another...

a Chain." Bulletin de lAcadamie Imperiale des Sciences de St. Petersburg, ser 6 (1913): 153162. Grinstead and Snell’s Introduction to Probability, page...

In probability theory and statistics, a probability distribution is a function that gives the probabilities of occurrence of possible events for an experiment...

catalog of articles in probability theory. For distributions, see List of probability distributions. For journals, see list of probability journals. For contributors...

contained in the likelihood function. A likelihood function arises from a probability density function considered as a function of its distributional parameterization...

or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for sampling from a specified multivariate probability distribution when direct sampling...