Eikosstatistics & data science

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

Time series: forecasting with linear models

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Introduction Time Series Modeling · Econometrics and Machine Learning

Overview

Topics covered

  • Introduction
  • Time series and linear models
  • Mathematical foundations of time series
  • Partial Autocorrelation Function (FACP)
  • Ergodicity
  • The General Linear Model and the invertibility condition

Related concepts

Main connections

  • Time series & ARIMA
  • Variance & standard deviation
  • Linear algebra & matrices
  • Maximum likelihood estimation
  • Linear regression
  • Residual analysis & diagnostics

Compatible notation

Mathematical sample in LaTeX

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

(Xt1,Xt2,…,Xtk)=d(Xt1+h,Xt2+h,…,Xtk+h),
View LaTeX source(X_{t_1}, X_{t_2}, \dots, X_{t_k}) \ \eqd \ (X_{t_1+h}, X_{t_2+h}, \dots, X_{t_k+h}),