STAT317 ECON323

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 .
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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

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of the hours have zero rainfall?
Produce an ACF plot for this series. What does this tell you about rain- fall?
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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
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;
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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?
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