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How to Calculate Cross Correlation in R?

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In this article we will discuss how to calculate cross correlation in R programming language. Correlation is used to get the relation between two or more variables.

  • The result is 0, if there is no correlation between two variables
  • The result is 1, if there is positive correlation between two variables
  • The result is -1, if there is negative  correlation between two variables

Cross correlation is used to measure the relationship between a time series and a lagged version of another time series. We can calculate this by using the ccf() method.

Syntax:

ccf(data1,data2)

where, data1 and data2 may be a vector or a dataframe

Return:

It will result the auto correlation lag and plot

Example: Cross correlation between two vectors

R




# create the vector with 10 elements
data1=c(1:10)
 
# create the vector with 10 elements
data2=c(45:54)
 
# get ccf of the two data
print(ccf(data1,data2))


 Output:

Example : Auto correlation between two columns in the dataframe

R




# create the dataframe with 2 columns
data1=data.frame(a=c(1:10),b=c(23:32))
 
# get ccf of the two dataframe columns
print(ccf(data1$a,data1$b))


 Output:


Last Updated : 24 Dec, 2021
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