[R-sig-eco] correlating three time-series in R

[Bob O'Hara]

You can pass the columns to ccf() directly:

df <- data.frame(x=rnorm(6), y=rnorm(6))
ccf(df$x, df$y)
print(ccf(df$x, df$y))

You should probably also check the time series task view: 
<https://cran.r-project.org/web/views/TimeSeries.html>, in particular 
the zoo package, to see what can be done with irregular time series.

But with 6 data points I'd be surprised if you have the power to detect 
anything that doesn't jump out when you simply plot the data.

Bob


On 26/07/17 11:07, Tania Bird wrote:
> I have three data sets of abundances through time for plants, insects and
> reptiles.
> There are 6 samples over a ten year period (all taxa sampled at the same
> time).
> I recognise this is a small data set for time series.
> 
> I would like to correlate the time series to see if
> a) increases in abundance of one taxon are correlated to another, and
> b) to see if the correlation between plants:insects is greater than
> plants:reptiles.
> 
> I thought to use the cross-correlation function in R
> e.g.  ccf(insects, reptiles)
> 
> Currently the data is in one dataframe with time as one column and
> abundance of each taxa is the next three columns.
> 
> How do I convert the data to a time.series format as given in the R
> example?
> 
> How can I compare the two ccf outputs?
> 
> Thanks
> 
> Tania
> 
> 
> Tania Bird MSc
> *"There is a sufficiency in the world for man's need but not for man's
> greed" ~ Mahatma Gandhi*
> 
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> 
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-- 
Bob O'Hara
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