Dear all, I am trying to correlate a variable tau1 to a set of other variables (x1, x2, x3, x4), taking into account an interaction with time ('doy') and place ('region'), and taking into account dependency of data in time per object ID. My dataset looks like:
doy objectID region tau1 x1 x2 x3 x4 1 1 A 0.000000 0.08 0.3657 64.1 0.001100 1 2 C 0.000000 0.10 0.3150 74.3 0.000847 1 3 B 0.000000 0.07 0.3264 60.9 0.000854 1 4 B 0.000000 0.08 0.3058 63.2 0.000713 1 5 D 2.716998 0.11 0.2835 93.7 0.000660 .... 365 1 A 0.010000 0.06 0.5489 27.3 0.003878 365 2 C 0.234000 0.12 0.1798 23.1 0.000278 365 3 B 1.353500 0.09 0.3417 37.8 0.000271 365 4 B 0.000000 0.40 0.1347 13.4 0.000173 365 5 D 3.478008 0.21 0.2384 37.7 0.000703 The total dataset consists of 151,840 rows (365 days x 416 object ID's) Since the data is dependent in time per objectID, I use a GAMM model with an autocorrelation function. Since each variable x1, x2, etc. is dependent on time and place, I should incorporate this as well. Therefore I am wondering if the following gamm-model is correct for my situation: model <- gamm( tau1 ~ te( x1, by= doy ) + te( x1, by= factor( region ) ) + ... + te( x4, by= doy ) + te( x4, by= factor( region ) ) + factor( region ), correlation= corAR1(form= ~ doy|objectID ), na.action= na.omit ). Does anyone know if this is ok? Or should I use a model which also includes terms like " te( x1 ) + ... + te( x4 )". And is the correlation function correct? Thanks so much!! Jeroen -- View this message in context: http://r.789695.n4.nabble.com/Multiple-interaction-terms-in-GAMM-model-tp4672297.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.