ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

골드펠드-콴트 이분산성 검정 (Goldfeld-Quandt Test for Heteroskedasticity)×가중 최소 제곱법 (Weighted Least Squares, WLS)×
분야계량경제학통계학
계열Hypothesis testRegression model
기원 연도19651935
창시자Stephen Goldfeld & Richard QuandtAlexander Craig Aitken
유형F-ratio test for heteroskedasticityWeighted linear estimator
원전Goldfeld, S. M., & Quandt, R. E. (1965). Some tests for homoscedasticity. Journal of the American Statistical Association, 60(310), 539–547. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
별칭GQ Test, Goldfeld-Quandt Heteroskedasticity Test, Split-Sample Variance Ratio Test, Goldfeld-Quandt Homojenlik TestiWLS, weighted regression, heteroscedasticity-corrected OLS, variance-weighted least squares
관련33
요약The 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 suspected of driving variance, omitting a central block, fitting separate regressions on the two tail sub-samples, and comparing their residual variances via an F-ratio. The test is particularly well-suited to situations where the error variance is believed to increase or decrease monotonically with an observed regressor.Weighted Least Squares is a generalization of Ordinary Least Squares (OLS) regression that assigns each observation a weight inversely proportional to its error variance, thereby down-weighting high-variance data points and up-weighting precise ones. Introduced in its general matrix form by Alexander Craig Aitken in 1935, WLS is the canonical remedy when heteroscedasticity is present and the error variance structure is known or can be reliably estimated.
ScholarGate데이터셋
  1. v1
  2. 1 출처
  3. PUBLISHED
  1. v1
  2. 3 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: Goldfeld-Quandt Test · Weighted Least Squares. 2026-06-20에 다음에서 검색함: https://scholargate.app/ko/compare