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Factor Analysis×Uchambuzi wa Ushawishi (Umbali wa Cook, DFFITS, Leveraji)×Uthabiti wa Makadirio ya Kovariansi (MCD)×
NyanjaTakwimu za UtafitiTakwimuTakwimu
FamiliaProcess / pipelineRegression modelRegression model
Mwaka wa asili193119771999
MwanzilishiLouis Leon ThurstoneR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD)
AinaMethodRegression diagnosticRobust multivariate location-scatter estimator
Chanzo asiliaThurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press. DOI ↗Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗Rousseeuw, P. J. & Van Driessen, K. (1999). A Fast Algorithm for the Minimum Covariance Determinant Estimator. Technometrics, 41(3), 212-223. DOI ↗
Majina mbadalaEFA, CFA, latent variable modelingCook's distance, DFFITS, leverage, influential observation detectionminimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD)
Zinazohusiana354
MuhtasariFactor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data.Influence diagnostics are a family of post-fit measures that quantify how much each single observation affects a fitted regression. Cook's distance was introduced by R. Dennis Cook in 1977, with leverage and DFFITS formalised by Belsley, Kuh and Welsch in 1980, to flag the observations that most strongly pull the estimated coefficients.Robust Covariance via the Minimum Covariance Determinant (MCD) estimates a multivariate mean vector and covariance matrix that are not distorted by outliers. It was made practical by the Fast-MCD algorithm of Rousseeuw and Van Driessen (1999), building on Rousseeuw's earlier work on robust estimation.
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ScholarGateLinganisha mbinu: Factor Analysis · Influence Diagnostics · Robust Covariance (MCD). Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare