Hi, I was wondering if anyone could help me with a homework
problem from Time Series Analysis and its Applications with R
examples. The data is in the ASTSA package in R and the two
datasets are respectively called sales and lead.
3.16
Let St represent the monthly sales data in sales (n = 150), and
let Lt be the leading indicator in lead.
(A) Fit an ARIMA model to St , the monthly sales data. Discuss
your model fitting in a step-by-step fashion, presenting your
(a) initial examination of the data,
(b) transformations, if necessary,
(c) initial identification of the dependence orders and degree
of differencing,
(d) parameter estimation,
(e) residual diagnostics and model choice.
(B) Use the CCF and lag plots between ∇St and ∇Lt to argue that
a regression of ∇St on ∇Lt−3 is reasonable. [Note: In lag2.plot(),
the first named series is the one that gets lagged.]
(C) Fit the regression model ∇St = β0 + β1∇Lt−3 + xt , where xt
is an ARMA process (explain how you decided on your model for xt).
Discuss your results
