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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Muundo wa Kiotomatiki wa Mpito laini (STAR)×ARFIMA: Muundo wa Mfumo wa ARMA wenye Viwango vya Nusu×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19941980
MwanzilishiTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Granger & Joyeux (1980); Hosking (1981)
AinaNonlinear time-series regime-switching modelLong-memory time series model
Chanzo asiliaTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15–29. DOI ↗
Majina mbadalasmooth transition autoregressive model, LSTAR, ESTAR, logistic STARfractionally integrated ARMA, long-memory time series model, ARFIMA / FIGARCH, fractional differencing model
Zinazohusiana45
MuhtasariThe Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.ARFIMA is a time series model that captures long-memory behaviour using a fractional differencing parameter d, generalising the integer differencing of ARIMA. It was introduced by Granger and Joyeux (1980) and formalised by Hosking (1981) to describe series whose autocorrelations decay slowly rather than abruptly.
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ScholarGateLinganisha mbinu: STAR Model · ARFIMA Model. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare