Time Series


This chapter is devoted to time series analysis which deals with dependent data observed over time. Concepts of stationarity, autocovariance, autocorrelation, and partial autocorrelation are introduced. Examples of various ARMA models are given, and issues of estimation and forecasting for such models are addressed. A brief introduction to spectral analysis appears in the last section along with nonparametric estimation of the spectral density function.


Stationarity; ARMA models; Forecasting; Spectral Analysis

13.1 Introduction

In the previous chapters, except for random-effects models in Chapter 11, all the different types of statistical modeling and procedures are concerned with data sets consisting of ...

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