Fuzzy c-means - Fuzzy c-means is a clustering algorithm that assigns each observation a degree of membership in each of a chosen number of clusters.
G-prior - A g-prior, commonly called Zellner's g-prior, is a Bayesian prior for regression coefficients in a normal linear model whose covariance is proportional to...
Gamma distribution - The gamma distribution is a family of continuous probability distributions for positive quantities, commonly parameterized by a positive shape and a...
Gamma function ( G ) - The gamma function, conventionally written with the uppercase Greek letter Gamma, extends the factorial relationship beyond nonnegative integer arguments.
Gaussian error model - A Gaussian error model assumes that the difference between an observed response and its modeled mean follows a normal distribution under specified conditions.
Gaussian mixture model - A Gaussian mixture model, or GMM, represents a probability distribution as a weighted sum of Gaussian component distributions.
Gaussian Naive Bayes - Gaussian Naive Bayes is a classification method that combines Bayes' rule with a Gaussian model for each numerical feature within each class and a...
Gaussian process approximations - Gaussian process approximations are methods that make Gaussian process modeling computationally feasible when direct calculations are too expensive or...
Gaussian process emulator - A Gaussian process emulator is a statistical surrogate that learns the input-output behavior of a simulator using a Gaussian process model.
Gaussian Process Regression - Gaussian process regression is a probabilistic regression method that places a Gaussian process model over an unknown function and updates that model using...
Gaussian random variable - A Gaussian random variable is a random variable whose probability distribution is Gaussian, also called normal.
Gelbach decomposition - Gelbach decomposition is a regression method for dividing the change in a selected coefficient, between a base model and a fuller model, into additive...
General linear model - A general linear model represents numerical outcomes as linear combinations of unknown coefficients and specified predictors, plus errors.
General regression neural network - A general regression neural network, or GRNN, is a memory-based method for predicting numerical outcomes by combining the outcomes of stored training...
Generalized estimating equation - A generalized estimating equation, usually discussed in the plural as generalized estimating equations or GEE, estimates relationships between predictors...
Generalized likelihood uncertainty estimation - Generalized likelihood uncertainty estimation, or GLUE, is a framework for exploring uncertainty in model predictions by retaining multiple acceptable model...
Generalized linear model - A generalized linear model, or GLM, relates an outcome’s conditional mean to a linear combination of predictors through a link function, while specifying an...
Generalized p-value - A generalized p-value is a hypothesis-testing quantity constructed using a generalized test variable whose reference distribution removes dependence on...
Generalized pairwise comparisons - Generalized pairwise comparisons are methods for comparing two groups by evaluating pairs containing one observation from each group according to a...
Generalized Procrustes analysis - Generalized Procrustes analysis, or GPA, aligns several configurations of corresponding points to a common consensus by removing specified differences in...
Generalized randomized block design - A generalized randomized block design is a blocked experiment with replication of each treatment within each block.
Generated regressor - A generated regressor is an explanatory variable constructed using quantities estimated in an earlier statistical step, then used in a later model.
Geodemographic segmentation - Geodemographic segmentation groups geographical areas according to similarities in demographic, social, economic, or household characteristics.
Geometric data analysis - Geometric data analysis is an approach to multivariate statistics that represents data as weighted clouds of points and studies their geometry to understand...
Geometric median - The geometric median of a collection of points is a point that minimizes the sum of Euclidean distances to them.
Geomteric mean - The geometric mean is an average obtained by multiplying positive values and taking the root corresponding to the number of values.
German tank problem - The German tank problem is a statistical estimation problem in which an unknown population size is inferred from a sample of consecutive serial numbers.
Gini's mean difference - Gini’s mean difference is a measure of dispersion defined as the average absolute difference between pairs of observations.
Glejser test - The Glejser test is a regression diagnostic that investigates heteroscedasticity by relating the absolute residuals from a fitted model to selected...
Global calibration - Global calibration, in the computer-experiment sense used by the NIST engineering-statistics glossary, means developing a function that transforms a...
Gold standard - A gold standard is an accepted reference used to judge the correctness or quality of another result.
Goldfeld - Quandt test - The Goldfeld - Quandt test is a test for heteroscedasticity that compares residual variance estimates from two separately fitted regression subsamples.
Gompertz distribution - The Gompertz distribution is a continuous distribution for nonnegative event times whose hazard changes exponentially with time.
Goodman and Kruskal's gamma - Goodman and Kruskal's gamma is a measure of ordinal association based on concordant and discordant pairs of observations.
Goodnessoffit test - A goodness-of-fit test evaluates whether observed data are sufficiently inconsistent with a specified statistical model to provide evidence against it.
Graphical data editing - Graphical data editing is the use of graphs to identify potentially erroneous, inconsistent, or otherwise unusual data for investigation and possible...
Grid sampling - Grid sampling, in the OECD glossary sense used here, is a form of cluster sampling whose clusters are grid areas composed of basic cells arranged in a...
GRIM test - The GRIM test, short for granularity-related inconsistency of means, checks whether a reported mean is mathematically compatible with its stated sample...
Group testing - Group testing is a method for identifying items with a particular property by testing collections of items together.
Growth curve (statistics) - A growth curve in statistics describes how an outcome changes over time, often using repeated measurements from the same individuals or other units.
Growth function - The growth function of a binary hypothesis class gives the largest number of distinct label patterns that its classifiers can produce on a set of a given size.
Grubbs's test - Grubbs's test is a statistical test for a single unusually extreme observation in a univariate sample whose ordinary observations are assumed to come from...
Guttman scale - A Guttman scale is a cumulative measurement scale in which endorsing a more demanding item implies endorsing every less demanding item on the same ordered...
Gy's sampling theory - Gy's sampling theory is a framework for understanding and controlling errors when taking and preparing samples of heterogeneous particulate materials.
H-spread - The H-spread is the difference between the upper and lower hinges of a dataset.
Hahn estimator - In quality-control terminology, the Hahn estimator estimates outgoing nonconformance from acceptance-sampling data while allowing underlying lot quality to...
Hajek projection - The Hájek projection of a finite-variance statistic based on independent observations is its best mean-square approximation within the class of additive...
Half-normal distribution - The half-normal distribution describes the absolute value of a normally distributed variable centered at zero.