Materi Analisis Deret Waktu
Model ARMA
By Eni Sumarminingsih, SSi, MM
we say that {Yt} is a mixed autoregressive moving
average process of orders p and q, respectively; we
abbreviate the name to ARMA(p,q)
The ARMA(1,1)
Model
O Note that this autocorrelation function decays
exponentially as the lag k increases.
O The damping factor is φ, but the decay starts
from initial value ρ1, which also depends on θ.
O This is in contrast to the AR(1) autocorrelation,
which also decays with damping factor φ but
always from initial value ρ 0 = 1.
O For example, if φ = 0.8 and θ = 0.4, then ρ 1 =
0.523, ρ2 = 0.418, ρ3 = 0.335, and so on.
O Several shapes for ρk are possible, depending
on the sign of ρ1 and the sign of φ.
By Eni Sumarminingsih, SSi, MM
we say that {Yt} is a mixed autoregressive moving
average process of orders p and q, respectively; we
abbreviate the name to ARMA(p,q)
The ARMA(1,1)
Model
O Note that this autocorrelation function decays
exponentially as the lag k increases.
O The damping factor is φ, but the decay starts
from initial value ρ1, which also depends on θ.
O This is in contrast to the AR(1) autocorrelation,
which also decays with damping factor φ but
always from initial value ρ 0 = 1.
O For example, if φ = 0.8 and θ = 0.4, then ρ 1 =
0.523, ρ2 = 0.418, ρ3 = 0.335, and so on.
O Several shapes for ρk are possible, depending
on the sign of ρ1 and the sign of φ.