[R] multiple comparisons of time series data

[Kyle Hall]

I am interested in a statistical comparison of multiple (5) time series' 
generated from modeling software (Hydrologic Simulation Program Fortran). The 
model output simulates daily bacteria concentration in a stream. The multiple 
time series' are a result of varying our representation of the stream within 
the model.

Our main question is: Do the different methods used to represent a stream 
produce different results at a statistically significant level?

We want to compare each otput time series to determine if there is a 
difference before looking into the cause within the model.  In a previous 
study, the Kolmogorov-Smirnov k-sample test was used to compare multiple time 
series'.

I am unsure about the strength of the Kolmogorov-Smirnov test and I have set 
out to determine if there are any other tests to compare multiple time 
series'.

I know htat R has the ks.test but I am unsure how this test handles multiple 
comparisons.  Is there something similar to a pairwise.t.test with a 
bonferroni corection, only with time series data?

Does R currently (v 2.3.0) have a comparison test that takes into account the 
strong serial correlation of time series data?


Kyle Hall

Graduate Research Assistant
Biological Systems Engineering
Virginia Tech