Statistical Analysis of Time Series and Forecasting
Pergamenshchikov Serguei, Pchelintsev Evgeny · HAL (Le Centre pour la Communication Scientifique Directe) · 2023
In this course, we present the principal parts of the time series analysis. First, stationary processes and trends in times series are introduced. Then we consider the linear regression models for which we study the main problems such that point estimation, the construction of confidence intervals, hypothesis testing, and forecasting. In addition, big data models and the main methods for their analysis are presented. Finally, we introduce the autoregressive and moving average autoregressive processes (ARMA) and study their basic properties, including the problem of forecasting.