[R-sig-eco] Time series and GLS

[LisaB]

Thanks Kinsford.  I thought it would be appropriate.  As a follow up
question: My first thought is to set up the data file with three columns:
year, population (A,B), and nest success and then to input the following
formula: success.gls=gls(success~year*population).  This would allow me to
test for the effect of year for each population and then also test for
differences between the two populations.  My questions are 1) have I
specified the model right for those questions and 2) would the acf function
calculate the autocorrelation correctly even though my 'year' in the data
file is repeated twice (once for each value of nest success/population)? 
Thanks. Lisa (hope all is well with you)


Kingsford Jones wrote:
> 
> The gls function in nlme fits a general linear model, so yes you can
> have categorical predictors (the advantage over the lm function is the
> error covariance matrix may have non-zero off-diagonals, such as with
> an autocorrelation structure, and non-constant diagonals).
> 
> hth,
> Kingsford Jones
> 
> On Fri, Jan 1, 2010 at 2:44 PM, LisaB <lisabaril at hotmail.com> wrote:
>>
>> Hello -
>>
>> I need to analyze some time series data in an ANOVA framework, but am
>> unsure
>> of how to go about it.  I have data on nest success (response) over a 22
>> year period for two populations.  For each year I have one value of nest
>> success per population.  I am interested in determining 1) whether there
>> are
>> differences in nest success over time between these two populations and
>> 2)
>> what are the trends for each population over time.  My thought is to use
>> GLS
>> and model temporal autocorrelation if the acf function indicates this is
>> an
>> issue, but since population is a categorical variable I'm unsure if this
>> is
>> appropriate.  Any advice would be much appreciated. Thank you. Lisa
>>
>>
>>
>>
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