ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Ujian CUSUM: Mengesan Ketidakstabilan Parameter dalam Model Regresi×Ujian Chow untuk Pecah Struktur×
BidangEkonometrikEkonometrik
KeluargaHypothesis testRegression model
Tahun asal19751960
PengasasBrown, Durbin & EvansGregory C. Chow
JenisRecursive residual testTest for structural break in regression coefficients
Sumber perintisBrown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society: Series B, 37(2), 149–192. DOI ↗Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605. DOI ↗
AliasCumulative Sum Test, CUSUMSQ Test, Brown-Durbin-Evans Test, Kümülatif Toplam TestiChow breakpoint test, structural break test, Chow yapısal kırılma testi
Berkaitan32
RingkasanThe CUSUM (Cumulative Sum) and CUSUMSQ (Cumulative Sum of Squares) tests, introduced by Brown, Durbin, and Evans (1975), assess whether the coefficients of a linear regression model remain constant over time. They are standard tools in econometrics for detecting structural breaks, policy shifts, or regime changes in time-series data without requiring prior knowledge of when a break occurs.The Chow test, introduced by Gregory Chow in 1960, checks whether the coefficients of a linear regression are the same across two subsamples — that is, whether a structural break occurs at a known point such as a policy change, crisis, or regime shift. It compares the fit of a single pooled regression with the combined fit of two separate regressions; a large improvement from splitting indicates the relationship differs between the two periods or groups.
ScholarGateSet data
  1. v1
  2. 1 Sumber
  3. PUBLISHED
  1. v1
  2. 1 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: CUSUM Test · Chow Test. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare