Problems:
1. Consider the MA(m)-process, with equal weights 1/(m+1) at all lags, given by
Xt = Σmk=01/(m+1) Zt k
(a) Find the ad of this process.
(b) When m = 1 use SAS to simulate a realization of this process.
2. Consider the following models where {Zt} is a Gaussian white noise.
Xt = -.98 Xt 1 + Zt
Xt = -.98Z-1 + Zt
Xt = .6 Xt-i - 1.2Zt-1 + Zt
Xt = Xt-1 + .8 Xt-2 - .5 Zt-1 + Zt
(a) Find the acf and plot it for k = 0,1, ....,10
(b) Simulate a series of 100 observations from each of the models with σz2 = 1 and plot the sample acf for k = 0,....20.
3. Express the models in Problem 2 using the B operator.
4. Suppose that (Xt) is a stationary process with autocovariance function γx. Express the autocovariance function of the difference filter of first order ∇Xt = Xt - Xt-1 in terms of γx. Find it when γx(k) = λ|k|.
5. Prove or disprove the following process is weakly stationary:
(a) Zt = A sin(2Πt + θ) where A is a constant, and θ is a random variable that is uniformly distributed on [0,2Π].
(b) Zt = A sin(2Πt + 0) where A is a random variable with zero mean and unit variance, and θ is a constant.