Description
Objectives
The UC - Time Series is aimed at the students who wishes to gain the basic knowledge and tools to acquire the skills to describe, analyze, interpret and predict the future evolution of univariate time series, maintaining an intermediate mathematical level. To this end, it is intended that the students understand the issues that the temporal dependence between observations introduces in the statistical treatment of this type of data; and, on the other hand, to acquire the necesssary knowledge for a systematic approach to univariate time series analysis.
Syllabus
1. Introduction 1.1 What is a time series? 1.2 Examples of time series 1.3 Objectives of time series modeling 2. Basic concepts in univariate linear time series 2.1 Trends and seasonal components 2.2 Stationarity and autocorrelation function 2.3 Autoregressive moving-average (ARMA) models 2.4 Non-stationary and seasonal time series models 3. Nonlinear univariate time series 3.1 Why do we need nonlinear models? 3.2 A selection of nonlinear time series models
Prerequisites
Probability, Statistics, and Stochastic Processes.
Cross Competence Component
The UC allows the development of transversal competences on Critical Thinking, Creativity and Problem Solving Strategies, in class, in autonomous work and in the several evaluation components. The percentage of the final grade associated with these competences should be around 15%.
Ethical Principles
All members of a group are responsible for the group’s work. In any assessment, every student shall honestly disclose any help received and sources used. In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.