Course Outline

Forecasting with R

  • Introduction to Forecasting
  • Exponential Smoothing
  • ARIMA models
  • The forecast package

Package 'forecast'

  • accuracy
  • Acf
  • arfima
  • Arima
  • arima.errors
  • auto.arima
  • bats
  • BoxCox
  • BoxCox.lambda
  • croston
  • CV
  • dm.test
  • dshw
  • ets
  • fitted.Arima
  • forecast
  • forecast.Arima
  • forecast.bats
  • forecast.ets
  • forecast.HoltWinters
  • forecast.lm
  • forecast.stl
  • forecast.StructTS
  • gas
  • gold
  • logLik.ets
  • ma
  • meanf
  • monthdays
  • msts
  • na.interp
  • naive
  • ndiffs
  • nnetar
  • plot.bats
  • plot.ets
  • plot.forecast
  • rwf
  • seasadj
  • seasonaldummy
  • seasonplot
  • ses
  • simulate.ets
  • sindexf
  • splinef
  • subset.ts
  • taylor
  • tbats
  • thetaf
  • tsdisplay
  • tslm
  • wineind
  • woolyrnq

Requirements

Basic general maths and statistics skills

Programming in any languages recommended but not necessary

  14 Hours
 

Testimonials

Related Courses

Statistical and Econometric Modelling

  21 hours

Statistical Analysis using SPSS

  21 hours

HR Analytics for Public Organisations

  14 hours

Talent Acquisition Analytics

  14 hours

Econometrics: Eviews and Risk Simulator

  21 hours

Introduction to Data Visualization with Tidyverse and R

  7 hours

R for Data Analysis and Research

  7 hours

Analysing Financial Data in Excel

  14 hours

Excel For Statistical Data Analysis

  14 hours

Statistics Level 1

  14 hours

Statistics Level 2

  28 hours

Minitab for Statistical Data Analysis

  14 hours

Statistics for Researchers

  35 hours

Statistics with SPSS Predictive Analytics Software

  14 hours

Advanced Statistics using SPSS Predictive Analytics Software

  28 hours