HW 8

Q1.

For these questions, write out the differenced model and identify the structure.

a. (3 points)

\[x_t = x_{t-1} + w_t\]

b. (3 points)

\[x_t = bt + w_t\]

Q2. (10 points)

Fit an ARIMA model to the Lake Huron data set. Fully describe the results and detail all parameters in the model. How could this model be used to make predictions.

library(datasets)
library(forecast)
ggtsdisplay(LakeHuron)

Q3. (10 points)

Analyze the airplane data using a regression framework in auto.arima() to capture the trend and seasonal components. Describe all of the parameters in this model and use this model to predict the airline passengers totals for the next year.

ggtsdisplay(AirPassengers)

Q4. (536 only)

Continue working through your projects, this should be added to the existing, and growing, project document.

• Write out the statistical model that you plan to use for your project and address the following questions.
  • Will this be more focused on explanation or prediction?
  • What criteria will you use to select a model?