Eikosstatistics & data science

Time Series, Health & Evidence Synthesis · Time Series & Forecasting

Time series analysis · Box-Jenkins methodology

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Chart from the original guide

Overview

Topics covered

  • Introduction
  • The Box-Jenkins Methodology
  • Conceptual perspective and foundations of temporal analysis
  • First and Second Order Ergodicity
  • The Wold Decomposition Theorem
  • Linear Stationary Processes: AR, MA and ARMA

Related concepts

Main connections

  • Time series & ARIMA
  • Variance & standard deviation
  • Mean & expected value
  • Hypothesis testing
  • Residual analysis & diagnostics
  • Maximum likelihood estimation

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

γ(h)≡Cov(Xt,Xt+h)=E[(Xt−μ)(Xt+h−μ)],∀t,h∈ℤ.
View LaTeX source\gamma(h) \equiv \Cov(X_t, X_{t+h}) = \E\big[(X_t - \mu)(X_{t+h} - \mu)\big], \qquad \forall t, h \in \Z.