Time Series Analysis in R: SMA, EMA, and Theta Models

Part 1 of a full time series analysis curriculum

Ratings 3.50 / 5.00

Time Series Analysis in R: SMA, EMA, and Theta Models

What You Will Learn!

Enhanced familiarity with R environment and functions related to time series analysis
Create Simple Moving Average Models
Create Exponential Moving Averages with and without smoothing
Use R's Compound Exponential Modeling Ability
Understand And Use The Theta Model In R
Basic ARIMA Modeling And Knowledge Of Autoregression Concept
Use the Prophet Model (a la Facebook)
Gain General Coding And Stylistic Knowledge Of R

Description

In this course we explore R's capability to model time series data with some of the most basic and widely used model types. We'll learn what a simple moving average is and how R can take the analysis of data in this model to a higher level, then we move on to exponential models which are the most widely used types for financial market data. Finally generalizing the EMA model to compound modeling in R and introducing a newer more powerful Theta model as a tool.