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

[Tania Bird]

Thanks Bob
This is great,

The correlation does jump out when I plot it- I am just looking for a
quantified way of testing what I see. If there is a more appropriate test
I'd be happy to learn.

Many thanks



Tania Bird MSc
*"There is a sufficiency in the world for man's need but not for man's
greed" ~ Mahatma Gandhi*

https://www.linkedin.com/in/taniabird
https://taniabird.webs.com



On 26 July 2017 at 12:51, Bob O'Hara <bohara at senckenberg.de> wrote:

> 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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