Statistics — Page 19
Explore statistical methods, their assumptions, interpretation and limitations.
Research field
Method family
Gibbs Sampling for Model Comparison
Gibbs sampling for model comparison is a Bayesian MCMC approach that simultaneously samples from the space of competing models and their parameters. By augmenting the Gibbs sampler with a discrete model-index variable, posterior model proba...
Gibbs Sampling with Measurement Error
Gibbs sampling with measurement error is a Bayesian MCMC method that jointly estimates unknown true covariate values and model parameters when the observed data are corrupted by measurement error. By treating the latent true values as addit...
Gibbs Sampling with Missing Data
Gibbs sampling with missing data treats unobserved values as additional unknowns alongside model parameters and samples all of them jointly within a Markov chain Monte Carlo loop. The method alternates between drawing the missing values fro...
Global Co-Kriging
Global Co-Kriging is a multivariate geostatistical interpolation method that estimates an unsampled primary variable by exploiting its spatial cross-correlation with one or more secondary variables. Unlike local (moving-window) approaches,...
Global Getis-Ord Gi*
The Global Getis-Ord Gi* statistic measures the overall degree of spatial clustering of high or low values across an entire study region. It answers whether the study area, taken as a whole, exhibits significant concentration of high values...
Global Hot Spot Analysis
Global Hot Spot Analysis uses the Getis-Ord G statistic to determine whether high or low attribute values are spatially concentrated across an entire study area. It answers one question: is there overall clustering of high values (a hot spo...
Global Kriging
Global Kriging is the ordinary kriging interpolation procedure applied using all available sample points as the neighborhood — no spatial search window limits which data contribute to each prediction. It produces optimal linear unbiased pre...
Global Moran's I
Global Moran's I is the most widely used single-number summary of spatial autocorrelation across an entire study area. It compares the attribute value at each location with values at neighbouring locations using a spatial weights matrix, an...
Global Ordinary Kriging
Global Ordinary Kriging (GOK) is the canonical geostatistical interpolation method that estimates values at unsampled locations as a weighted linear combination of nearby observations. It fits a single variogram model to the entire dataset,...
Global Remote Sensing Classification
Global Remote Sensing Classification assigns every pixel across an entire image or worldwide dataset to a discrete land-cover or thematic class. Treating the scene uniformly — rather than adapting to local subregions — this wall-to-wall app...
Global Spatial Autocorrelation
Global Spatial Autocorrelation measures the degree to which similar values cluster together across an entire study area. Rather than identifying where clusters occur, it yields a single summary statistic — most commonly Moran's I — that qua...
Global Spatial Durbin Model
The Global Spatial Durbin Model extends the spatial lag model by including not only a spatially lagged dependent variable but also spatially lagged independent variables (WX). A single set of global coefficients applies uniformly across all...
Global Spatial Error Model
The Global Spatial Error Model (SEM) is a spatial regression technique that accounts for spatially autocorrelated error terms using a single, globally constant spatial parameter. It separates genuine predictor effects from spatial nuisance...
Global Spatial Panel Model
The Global Spatial Panel Model extends panel data regression by incorporating a global spatial weights matrix that links every location to every other location simultaneously. It jointly accounts for cross-sectional spatial dependence, time...
Global Universal Kriging
Global Universal Kriging is a geostatistical interpolation method that models a spatially varying trend (drift) as a deterministic function of coordinates and uses the entire dataset to fit both the trend coefficients and the residual vario...
Global VAR
Global VAR (GVAR) is a large-scale macroeconomic modeling framework linking multiple countries (or regions) via trade and financial channels, allowing shocks in one country to propagate through the global system. Introduced by Pesaran et al...
Goldfeld-Quandt Test
The Goldfeld-Quandt test, introduced by Stephen Goldfeld and Richard Quandt in 1965, is a classical diagnostic procedure for detecting heteroskedasticity in OLS regression. It operates by sorting observations according to a variable suspect...
Gompertz-Makeham Law of Mortality
The Gompertz-Makeham law is the foundational parametric model of adult human mortality. Benjamin Gompertz showed in 1825 that the force of mortality rises exponentially with age, and William Makeham added an age-independent background term...
Goodman Association Model
Goodman's association models, especially the row-column (RC) model, analyze the association in a two-way contingency table by representing it as a product of estimated scores for the row categories and scores for the column categories, scal...
Granger Causality
The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictiv...
Granger Causality Test
The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 196...
Gravity Model of Migration
The gravity model of migration explains the volume of movement between two places as proportional to the product of their populations (masses) and inversely proportional to the distance separating them, by direct analogy to Newton's law of...
Gravity Model of Tourist Flows
The gravity model of tourist flows explains travel between an origin and a destination by analogy to Newton's law of gravitation: bilateral flows increase with the economic 'mass' of both the origin and the destination and decrease with the...
Gravity Model of Trade
The gravity model of trade explains bilateral trade flows by analogy to Newton's law of gravitation: trade between two economies is proportional to their economic sizes and inversely related to the trade costs (such as distance) between the...