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*
correlating three time-series in R
4 messages · Bob OHara, Tania Bird, Thomas Petzoldt
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* [[alternative HTML version deleted]]
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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*
[[alternative HTML version deleted]]
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-- Bob O'Hara NOTE: this email will die at some point, so please update you records to bob.ohara at ntnu.no Institutt for matematiske fag NTNU 7491 Trondheim Norway Mobile: +49 1515 888 5440 Journal of Negative Results - EEB: www.jnr-eeb.org
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Hi, a compact, practical and well readable introduction to some time series methods can be found in chapter 6 of Kleiber and Zeileis (2008): Applied Economics with R. This book is also well suited for ecologists and builds a fundamental for further reading and understanding. Thomas Am 26.07.2017 um 12:05 schrieb 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*
[[alternative HTML version deleted]]
_______________________________________________ R-sig-ecology mailing list R-sig-ecology at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
-- Bob O'Hara NOTE: this email will die at some point, so please update you records to bob.ohara at ntnu.no Institutt for matematiske fag NTNU 7491 Trondheim Norway Mobile: +49 1515 888 5440 Journal of Negative Results - EEB: www.jnr-eeb.org
Thomas Petzoldt Technische Universitaet Dresden Faculty of Environmental Sciences Institute of Hydrobiology 01062 Dresden, Germany http://tu-dresden.de/Members/thomas.petzoldt -- limnology and ecological modelling --