Reader small image

You're reading from  Practical Predictive Analytics

Product typeBook
Published inJun 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785886188
Edition1st Edition
Languages
Tools
Right arrow
Author (1)
Ralph Winters
Ralph Winters
author image
Ralph Winters

Ralph Winters started his career as a database researcher for a music performing rights organization (he composed as well!), and then branched out into healthcare survey research, finally landing in the Analytics and Information technology world. He has provided his statistical and analytics expertise to many large fortune 500 companies in the financial, direct marketing, insurance, healthcare, and pharmaceutical industries. He has worked on many diverse types of predictive analytics projects involving customerretention, anti-money laundering, voice of the customer text mining analytics, and health care risk and customer choice models. He is currently data architect for a healthcare services company working in the data and advanced analytics group. He enjoys working collaboratively with a smart team of business analysts, technologists, actuaries as well as with other data scientists. Ralph considered himself a practical person. In addition to authoring Practical Predictive Analytics for Packt Publishing, he has also contributed two tutorials illustrating the use of predictive analytics in Medicine and Healthcare in Practical Predictive Analytics and Decisioning Systems for Medicine: Miner et al., Elsevier September, 2014, and also presented Practical Text Mining with SQL using Relational Databases, at the 2013 11th Annual Text and Social Analytics Summit in Cambridge, MA. Ralph resides in New Jersey with his loving wife Katherine, amazing daughters Claire and Anna, and his four-legged friends, Bubba and Phoebe, who can be unpredictable. Ralph's web site can be found at ralphwinters.com
Read more about Ralph Winters

Right arrow

Simple moving average


A simple moving average will simply take the sum of the time series variable for the last k periods and then will divide it by the number of periods. In this sense, it is identical to the calculation for the mean. However, what makes it different from a simple mean is the following:

  • The average will shift for every additional time period. Moving averages are backward-looking, and every time a time period shifts, so will the average. That is why they are called moving. Moving averages are sometimes called rolling averages.
  • The look backwards period can shift. That is the second characteristic of a moving average. A 10-period moving average will take the average of the last 10 data elements, while a 20-period moving average will take the sum of the last 20 data points, and then divide by 20.

Computing the SMA using a function

To compute a rolling five-period moving average for our data, we will use the simple moving average (SMA) function from the TTR package, and then display...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Practical Predictive Analytics
Published in: Jun 2017Publisher: PacktISBN-13: 9781785886188

Author (1)

author image
Ralph Winters

Ralph Winters started his career as a database researcher for a music performing rights organization (he composed as well!), and then branched out into healthcare survey research, finally landing in the Analytics and Information technology world. He has provided his statistical and analytics expertise to many large fortune 500 companies in the financial, direct marketing, insurance, healthcare, and pharmaceutical industries. He has worked on many diverse types of predictive analytics projects involving customerretention, anti-money laundering, voice of the customer text mining analytics, and health care risk and customer choice models. He is currently data architect for a healthcare services company working in the data and advanced analytics group. He enjoys working collaboratively with a smart team of business analysts, technologists, actuaries as well as with other data scientists. Ralph considered himself a practical person. In addition to authoring Practical Predictive Analytics for Packt Publishing, he has also contributed two tutorials illustrating the use of predictive analytics in Medicine and Healthcare in Practical Predictive Analytics and Decisioning Systems for Medicine: Miner et al., Elsevier September, 2014, and also presented Practical Text Mining with SQL using Relational Databases, at the 2013 11th Annual Text and Social Analytics Summit in Cambridge, MA. Ralph resides in New Jersey with his loving wife Katherine, amazing daughters Claire and Anna, and his four-legged friends, Bubba and Phoebe, who can be unpredictable. Ralph's web site can be found at ralphwinters.com
Read more about Ralph Winters