ScholarGate
Асистент

Порівняння методів

Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.

Модель Марковського перемикання режимів (MS-AR / MS-VAR)×Порогова та згладжена VAR (TVAR / STVAR)×Модель векторної авторегресії (VAR)×
ГалузьЕконометрикаЕконометрикаЕконометрика
РодинаRegression modelRegression modelRegression model
Рік появи198919982005
Автор методуHamilton (1989); Kim & Nelson (1999)Tsay (multivariate threshold modelling)Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
ТипRegime-switching time series modelNonlinear multivariate time-series modelMultivariate time-series model
Основоположне джерелоHamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Інші назвиregime-switching model, Markov-switching autoregression, MS-AR, MS-VARTVAR, STVAR, regime-switching VAR, threshold VARvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Пов'язані554
ПідсумокThe Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions.Threshold VAR and Smooth-Transition VAR are nonlinear multivariate time-series models in which the coefficients of a vector autoregression switch between regimes according to a threshold variable. Building on Tsay's 1998 treatment of multivariate threshold models, they capture different dynamic structures across phases such as the business cycle, financial crises, or policy differences.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
ScholarGateНабір даних
  1. v1
  2. 2 Джерела
  3. PUBLISHED
  1. v1
  2. 2 Джерела
  3. PUBLISHED
  1. v1
  2. 1 Джерела
  3. PUBLISHED

Перейти до пошуку Завантажити слайди

ScholarGateПорівняння методів: Markov-Switching Model · Threshold and Smooth-Transition VAR · VAR Model. Отримано 2026-06-19 з https://scholargate.app/uk/compare