ScholarGate
المساعد

قارن الطرق

راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.

تحليل العوامل×تشخيصات التأثير (مسافة كوك، DFFITS، الرافعة المالية)×تقدير التغاير المتين (MCD)×
المجالإحصاء البحثالإحصاءالإحصاء
العائلةProcess / pipelineRegression modelRegression model
سنة النشأة193119771999
صاحب الطريقةLouis Leon ThurstoneR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD)
النوعMethodRegression diagnosticRobust multivariate location-scatter estimator
المصدر التأسيسيThurstone, 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 ↗
الأسماء البديلةEFA, CFA, latent variable modelingCook's distance, DFFITS, leverage, influential observation detectionminimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD)
ذات صلة354
الملخصFactor 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.
ScholarGateمجموعة البيانات
  1. v1
  2. 3 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED

انتقل إلى البحث تنزيل الشرائح

ScholarGateقارن الطرق: Factor Analysis · Influence Diagnostics · Robust Covariance (MCD). استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare