STA 4853/5856 HW 3 Partial Solutions · Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of...
Transcript of STA 4853/5856 HW 3 Partial Solutions · Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of...
Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of 2Time Series STA 4953/5856
◦ π(z) from Slide 10 on Feb 6 (2 points) Write π(z) = 1−.9z1+.5z
as an infinite series.
• Using the geometric series for the denominator, we have
π(z) = (1− .9z)∞∑
j=0
(−.5)jzj
= (1− .9z)(1− .5z + .52z2 − .53z3 + · · · )= 1− (.5 + .9)z + (.5(.9) + .52)z2 − (.52(.9) + .53) + · · ·= 1− (.5 + .9)z + .5(.9 + .5)− .52(.9 + .5) + · · ·
= 1− 1.4∞∑
j=1
(−.5)j−1zj
◦ #3.14(a) (4 points) Verify if the following models are stationary, invertible, or both.
(i) (1−B)Zt = (1− 1.5B)at
(ii) (1− .8B)Zt = (1− .5B)at
(iv) (1− .6B)Zt = (1− 1.2B + .2B2)at
• For stationary (resp. invertibility) the roots of φ(B) (resp. θ(B)) should lie outside the unit disk.
(i) φ(B) = 1 − B has a unit root (since φ(1) = 0) and therefore the process is not stationary.The root of θ(B) = 1 − 1.5B is 2/3 which is smaller than one in absolute value, and thereforethis process is not invertible either.
(ii) This part is not graded.
(iv) The polynomial φ(B) = 1− .6B has root 1/.6 = 5/3 which is bigger than one in absolute value,and therefore this process is stationary. The θ(B) polynomial factors as
θ(B) =1
5(B − 1)(B − 5)
and because one of the roots is 1, the process is not invertible.
◦ #3.14(b,c) for (i) Consider the ARMA(1,1) process
(1−B)Zt = (1− 1.5B)at
(a) Express the model in an MA representation if it exists.
(b) Express the model in an AR representation if it exists.
• This process is neither stationary nor invertible, so neither representation exists.
◦ Exponential Smoothing (2 points) Show that the process
Zt = µ+ α∑j<t
aj + at
is ARIMA(0,1,1).
Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 2 of 2Time Series STA 4953/5856
• Computing the difference of Zt gives
∇Zt = Zt − Zt−1
= µ+ α∑j<t
+at −
(µ+ α
∑j<t−1
aj + at
)= αat−1 + at − at−1
= at + (α− 1)at−1
which is a MA(1) process. Therefore Zt is ARIMA(0,1,1).
◦ #4.5 (2 points) Consider the simple white noise process, Zt = at. Discuss the consequences by exam-ining the ACF, PACF, and AR representation of the differenced series, Wt = Zt − Zt−1.
• Only the ACF of Wt is graded. The differenced series Zt = at − at−1 is MA(1) and therefore has anACF given by
ρk =
{−12, k = 1
0, k > 0
(with the usual ρ0 = 1 and ρ−k = ρk).