Simple moving average program

Step First of all go through the data table given in below image. Thank you for reading…Keep visiting Techiequality. Popular Post:. Your email address will not be published. Save my name, email, and website in this browser for the next time I comment.

Notify me of follow-up comments by email. Notify me of new posts by email. I figured it would turn the stomach of a real math guy but, it turns out it is one of the accepted ways of doing it.

And it works well. Just remember that the higher your "length" the slower it is following what you want to follow. That may not matter most of the time but when following satellites, if you are slow, the trail could be far from the actual position and it will look bad.

You could have a gap between the sat and the trailing dots. I chose a length of 15 updated 6 times per minute to get adequate smoothing and not get too far from the actual sat position with the smoothed trail dots. At this point I was satisfied that I was able to defend that answer as the optimal solution in some aspects. But then I noted that he was doing some complicated stuff there, combining some subsampling and exponential averaging, and actually did not satisfy the "no-buffer" requirement.

Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Learn more. How to implement a moving average in C without a buffer? Ask Question. Asked 6 years, 11 months ago. Active 3 months ago. Viewed 66k times. Improve this question. Matt L. Add a comment. Active Oldest Votes. Improve this answer.

Moving average refers to a series of averages of fixed size subsets of the total set of observations. It is also known as rolling average, running average, rolling means or running average.

Consider the set of n observations and k be the size of the window for determining the average at any time t. Then moving average list is calculated by initially taking the average of the first k observations present in the current window and storing it in the list. Now, the window is expanded according to the condition of the moving average to be determined and again average of the elements present in the window is calculated and stored in the list. This process is continued until the window has reached the end of the set.

We will first calculate average of first 3 elements and that will be stored as first moving average. Then window will be shifted one position to the right and again average of elements present in the window will be calculated and stored in the list.

Similarly, the process will repeat till the window reaches the last element of the array. Following is the illustration of the above approach: Below is the implementation:. It is used for analyzing trends. It provides a method called numpy.

A moving average can be calculated by finding the sum of elements present in the window and dividing it with window size. It provides a method called pandas.

The mean of the window can be calculated by using pandas. It is used for time series analysis. A moving average can be calculated by dividing the cumulative sum of elements by window size.

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