Calculating Autocorrelations for Large Data Sets in Excel: Tips and Alternatives

In summary, the individual is seeking help to calculate autocorrelations for a set of equi-spaced data points using Excel, but the formula does not work for all lags. They are also looking for alternative programs such as Mathematica, Python, Scilab, Octave, and Freemat to help with this task.
  • #1
MichalXC
41
0
I have a set of 9,999 equi-spaced data points, and I would like to calculate the autocorrelations for ALL lags up to 5,000.

In Excel, I want to have this code:

=CORREL(B1:B9998,B2:B9999)
=CORREL(B1:B9997,B3:B9999)
=CORREL(B1:B9996,B4:B9999)
...
=CORREL(B1:B5000,B5000:B9999)

Unfortunately, the formula does not "translate" nicely when I extend it downwards.

Also I have Excel 2008 for Mac, which does not handle VB Macros.

Can anyone direct me? Or suggest a better way of doing it? I don't have MatLab, but I do have Mathematica.

Thanks in advance.
 
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  • #2
Well, I am going to suggest Python, but only because you thought of Matlab, in the first place...which shows that you might be inclined to some scripting.

Actually, there is FreeMat which is an a-la-matlab application.

But also, there is Python with its numpy and scipy (scipy.stats) modules you can do anything you want and plot it right away with matplotlib.

...just a thought
 
  • #3
Try:
=CORREL(OFFSET($B$1, 0, 0, 9999-A1, 1 ),OFFSET($B$1, A1, 0, 9999-A1, 1 ))
=CORREL(OFFSET($B$1, 0, 0, 9999-A2, 1 ),OFFSET($B$1, A2, 0, 9999-A2, 1 ))

after you have filled column A with the consecutive row numbers (1, 2, 3, ...)
 
  • #4
Gsal, sorry, I don't know Python.

The above-posted formula works great though!

Thanks, both, for your replies!
 
  • #5
Glad to be of help! :smile:
 
  • #6
Hi again.

Excel (understandably) becomes unresponsive when asked to do some of these calculations. Seeing as much, I would be most grateful if someone could show me how to implement a correlogram (autocorrelation plot) in Mathematica.
 
  • #7
since you mentioned MATLAB (deja vu?), another program you might want to check out is Scilab. not a full clone, but very similar to matlab.
 
  • #8
Then, there is Octave and Freemat. And of course, Python with numpy/scipy.
 

What is autocorrelation?

Autocorrelation is a statistical method used to measure the relationship between a variable and its past values. It is also known as serial correlation because it measures how a variable is correlated with itself over time.

How is autocorrelation calculated in Excel?

In Excel, autocorrelation can be calculated by using the CORREL function. This function takes two arguments: the range of data and the lag value, which represents the number of time periods between each data point and its corresponding past value. The result is a correlation coefficient that ranges from -1 to 1.

What does a positive/negative autocorrelation coefficient indicate?

A positive autocorrelation coefficient indicates a positive relationship between a variable and its past values, meaning that as one increases, the other also tends to increase. On the other hand, a negative autocorrelation coefficient indicates a negative relationship, where an increase in one variable is associated with a decrease in the other.

Why is autocorrelation important in data analysis?

Autocorrelation is important in data analysis because it helps identify patterns and trends in time series data. It also allows us to make predictions about future values based on past values, which can be useful in forecasting and decision making.

What are some limitations of using autocorrelation in data analysis?

Autocorrelation assumes that the relationship between a variable and its past values is linear, which may not always be the case. It also does not take into account other variables that may affect the relationship. Additionally, autocorrelation can be influenced by outliers and non-stationarity of data, which can lead to inaccurate results.

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