本次澳洲统计代写主要是完成臭氧厚度数据的时间序列分析

MATH1318 Time Series Analysis Assignment

您将在此作业中分析的数据集表示以Dobson单位表示的1927年至2016年臭氧层厚度的年度变化。数据集中的负值表示厚度减小,正值表示厚度增加。

您将独立完成此任务,以使用此处提供的臭氧厚度系列执行以下任务。

任务1:检查模块1和2的内容,以执行以下操作:

通过执行模块1中的模型构建策略,在线性,二次方,余弦,周期性或季节性趋势模型(模块2中介绍)中找到最佳拟合模型。
使用您发现的最佳模型对未来5年的年度变化进行预测。

任务2:查看模块3、4和5的内容,以执行以下操作:

使用模块5中涵盖的所有合适的模型规范工具,提出一组可能的ARIMA(p,d,q)模型。模块3中说明了ARMA模型,模块4中说明了ARIMA模型。在此任务中,您应演示使用每个模型规格工具(例如ACF-PACF,EACF,BIC表)均应清楚并编写清晰正确的注释,以支持您对(p,d,q)订单的选择。

准备一份报告,其中包括适当的部分,例如简介,结论,附录和每项任务的一章。只要报告结构合理,结构整齐,报告的结构就由您决定。此处期望的报告不是简短的业务报告或论文。您可以在此处参考RMIT资源以获取有关报告编写的更多信息。具体来说,此处链接中“示例报告结构”下的“科学报告”可能是预期报告的一个很好的示例。

下面给出的主题将指导您完成我在报告,R代码,描述性分析,建模和诊断检查方面的期望。

与课程学习成果(CLO)的关系:

这项作业将有助于以下课程学习成果:

CLO1。以图表和摘要统计的信息方式提供当前时间序列; CLO3。估计模型参数,并比较针对同一数据集开发的不同模型的估计和预测准确性;
CLO4。准备口头和书面报告以呈现时间序列分析的结果。

提交说明:

所有报告必须通过Turnitin提交。
您的提交应以PDF或Microsoft Word文件的形式上传。

Instructions

The dataset you will analyse in this assignment represents yearly changes in the thickness of Ozone layer 1927 to 2016 in Dobson units. A negative value in the dataset represents a decrease in the thickness and a positive value represents an increase in the thickness.

You will work independently on this assignment to do the following tasks using the ozone thickness series available here .

Task 1: Review the contents of Module 1 and 2 to do the following:

Find the best fitting model among the linear, quadratic, cosine, cyclical or seasonal trend models (covered in Module 2) by implementing the model-building strategy in Module 1.
Give the predictions of yearly changes for the next 5 years using the best model you find.

Task 2: Review the contents of Module 3, 4 and 5 to do the following:

Propose a set of possible ARIMA(p, d, q) models using all suitable model specification tools covered in Module 5. ARMA models are explained in Module 3 and ARIMA models are explained in Module 4. In this task, you should demonstrate use of each model specification tool such as ACF-PACF, EACF, BIC table clearly and write clear and correct comments to back up your choices of (p, d, q) orders.

Prepare a report that includes proper sections such as Introduction, Conclusion, Appendix and a chapter for each task. The structure of the report is up to you as long as it is a well-structured and neat report. The report expected here is not a short business report or not an essay. You can refer to the RMIT resource here  for further information on report writing. Specifically, “Science Report” under “Sample report structures” in the link here may be a good example for the report expected.

The rubric given below will guide you through my expectations in terms of reporting, R codes, descriptive analysis, modelling, and diagnostic checking.

Relation to Course Learning Outcomes (CLOs):

This assignment will contribute to the following course learning outcomes:

CLO1. Present time series in an informative way, both graphically and with summary statistics; CLO3. Estimate model parameters and compare different models developed for the same dataset in terms of their estimation and prediction accuracy;
CLO4. Prepare both oral and written reports to present results of time-series analyses.

Submission Instructions:

All reports must be submitted via the Turnitin.
Your submission should be uploaded as a PDF or Microsoft Word file.


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