Decoupling (probability), the Glossary
In probability and statistics, decoupling is a reduction of a sample statistic to an average of the statistic evaluated on several independent sequences of the random variable.[1]
Table of Contents
9 relations: Conditional probability, Coupling (probability), Independence (probability theory), Probability theory, Random variable, Statistic, Statistics, Stochastic process, U-statistic.
- Statistical theory
Conditional probability
In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) is already known to have occurred.
See Decoupling (probability) and Conditional probability
Coupling (probability)
In probability theory, coupling is a proof technique that allows one to compare two unrelated random variables (distributions) and by creating a random vector whose marginal distributions correspond to and respectively.
See Decoupling (probability) and Coupling (probability)
Independence (probability theory)
Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes.
See Decoupling (probability) and Independence (probability theory)
Probability theory
Probability theory or probability calculus is the branch of mathematics concerned with probability.
See Decoupling (probability) and Probability theory
Random variable
A random variable (also called random quantity, aleatory variable, or stochastic variable) is a mathematical formalization of a quantity or object which depends on random events.
See Decoupling (probability) and Random variable
Statistic
A statistic (singular) or sample statistic is any quantity computed from values in a sample which is considered for a statistical purpose.
See Decoupling (probability) and Statistic
Statistics
Statistics (from German: Statistik, "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data.
See Decoupling (probability) and Statistics
Stochastic process
In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a sequence of random variables in a probability space, where the index of the sequence often has the interpretation of time.
See Decoupling (probability) and Stochastic process
U-statistic
In statistical theory, a U-statistic is a class of statistics defined as the average over the application of a given function applied to all tuples of a fixed size.
See Decoupling (probability) and U-statistic
See also
Statistical theory
- Algebraic statistics
- Ancillary statistic
- Asymptotic theory (statistics)
- Average variance extracted
- Bayesian statistics
- Big O in probability notation
- Classical test theory
- Completeness (statistics)
- Conditional expectation
- Decoupling (probability)
- Deficiency (statistics)
- Degrees of freedom (statistics)
- Design of experiments
- Directional statistics
- Dudley's entropy integral
- Empirical characteristic function
- Extreme value theory
- Generalizability theory
- Generalized renewal process
- Goodness of fit
- Independent and identically distributed random variables
- Information theory
- Likelihood
- MAGIC criteria
- Mathematical statistics
- Multivalued treatment
- Negative log predictive density
- Observational equivalence
- Optimal experimental design
- Pivotal quantity
- Probability interpretations
- Quadratic form (statistics)
- Statistical assumption
- Statistical inference
- Statistical interference
- Statistical model
- Statistical models
- Statistical population
- Statistical randomness
- Statistical theory
- Sufficient statistic
- Theory of conjoint measurement
- Uncertain data
- Uncertainty quantification