Written Assignment 4
Complete Exercise 6 at the end of Chapter 6 in the textbook. Then, write a paper that reconstructs a time series forecast. Cite at least one outside source to answer the last part of the assignment, in which you are asked to compare forecasts from stlf() with those from snaive(), using a test set comparing the last two years of data. Which is better? Also, what errors discussed in this module, if any, could occur when creating this forecast?
Your paper should be written in narrative form in APA style.
Exercise 6
We will use the bricksq data (Australian quarterly clay brick production. 1956–1994) for this exercise.
Use an STL decomposition to calculate the trend-cycle and seasonal indices. (Experiment with having fixed or changing seasonality.)
Compute and plot the seasonally adjusted data.
Use a naïve method to produce forecasts of the seasonally adjusted data.
Use stlf() to reseasonalise the results, giving forecasts for the original data.
Do the residuals look uncorrelated?
Repeat with a robust STL decomposition. Does it make much difference?
Compare forecasts from stlf() with those from snaive(), using a test set comprising the last 2 years of data. Which is better?
