This is a paper that focuses on the forecast of a dataset of a single time series between algorithms. The paper also requires documentation of the forecasting process in a research report.
Forecast of a dataset of a single time series between algorithms
Coursework Information & Submission
This is an individual assignment weighted 100%. Standard departmental penalties will apply for late work unless you have been given an extension for exceptional reasons from the course administrator. All submissions check will be by the plagiarism software. Submit your report PLUS R scripts in the appendix through in Moodle.
Task: Forecast 1 Real-Word Time Series – 100%
You are to forecast a dataset of a single time series individually assigned to you in a miniature competition between the algorithms. Your objective is to:
(a) Develop the most accurate statistical forecasting models, demonstrating your modelling skills!
Firstly, obtain your time series from the respective competition dataset
o Download the datasets from the Moodle website
o Select the 1 time series allocated to you from the competition file
Secondly, construct forecasts, and for each of the time series
Thirdly, conduct a thorough exploratory data analysis (using graphs, statistical test, etc. and a verbal analysis)
Fourthly, build multiple potentially suitable forecasting models, including a suitable Exponential Smoothing, ARIMA, and Time Series Regression model to predict the 14 next values (2 weeks ahead)
Lastly, choose what you assume to be the “best” model from these models for a final submission, by assessing errors and comparing errors against a Naive and a Seasonal Naive benchmark models.
(b) Document your forecasting process in a technical research report
• Write a technical report to document your model building skills and also to justify your choice of model
• Critically discuss some findings and choices
Finally, ensure that you include references from the sources that you will use in the assignment paper. Also, ensure the references are on their own page from the rest of the assignment.