Assignment 3
STAT317/ECON323
Due 5pm Monday, 4 October 2021
A reminder that graphs help in interpretation and explanation and you are expected to present them properly.
1 Question 1 – 11 Marks
For assignment 3 I have supplied a text file (rainfall.dat). This has the hourly rainfall data at Christchurch for .
a b
c
d e
Get the data from the text file into an R time series object.
Since most of the time the hourly rainfall is zero (0) this are not in the file. Create a complete time series with all 8,784 hours in the year. That is, add the hours with zero rainfall. Plot this series. Also what percentage of the hours have zero rainfall?
Produce an ACF plot for this series. What does this tell you about rain- fall?
From the hourly data create a time series of daily data
Produce an ACF plot for the daily rainfall series? Comparing it with previous ACF how similar or dissimilar are they? Explain your result?
Question 2 – 9 marks
2
For this question use the time series you selected for the previous assignments. Use the data from the years 2000-2019 only i.e. suppress COVID effects. It is recommended you use the HoltWinters option in the forecast package.
a Fit the following models to your data using the following methods:
(a) Single exponential smoothing
(b) Exponential Smoothing with trend
(c) Exponential Smoothing with trend and seasonal component (d) The previous model but applied to a log transformed series;
1
For each of the models, is the time series of the residuals what you would expect for a proper time series model fit? Also from the residuals, which do you think is the best model? Explain your reasoning.
b For model 1(d) what are the values of for α,β,γ? What does this tell you about the weighting for measured recent data compared to that for estimates?
2