Dear R-community, I'm analysing some noise using the nlme-package. I'm writing in order to get my usage of lme verified.
In practise, a number of samples have been processed by a machine measuring the same signal at four different channels. I want to model the noise. I have taken the noise (the signal is from position 1 to 3500, and after that there is only noise). My data looks like this: channel.matrix: pos channel0 channel1 channel2 channel3 samplenumber 1 3501 8 3 12 1 1 2 3502 3 7 0 14 1 3 3503 9 1 13 3 1 4 3504 3 7 3 14 1 5 3505 6 5 4 5 1 6 3506 7 0 16 0 1 ... 495 3995 5 2 9 9 1 496 3996 2 4 6 10 1 497 3997 3 2 7 7 1 498 3998 2 4 3 9 1 499 3999 3 1 6 11 1 500 4000 0 3 6 7 1 2301 3501 1 4 3 9 2 2302 3502 3 3 4 13 2 2303 3503 4 1 8 5 2 2304 3504 3 1 10 2 2 2305 3505 2 3 5 8 2 2306 3506 0 5 8 2 2 ... The model is channel0 ~ alpha_i + eps_{i, j} + channel1 + channel2 + channel3 where i is sample number, j is position, and: alpha_i: fixed effect for each samplenumber eps_{i, j}: random effect, here with correlation structure as AR(1) channel1, ..., channel3: fixed effect for each channel not depending on samplenumber nor position (And then afterwards I would model channel1 ~ ... + channel2 + channel3 etc.) I then use this function call: channel.matrix.grouped <- groupedData(channel0 ~ pos | samplenumber, data = channel.matrix) fit <- lme(channel0 ~ pos + samplenumber + channel1 + channel2 + channel3, random = ~ pos | samplenumber, correlation = corAR1(value = 0.5, form = ~ pos | samplenumber), data = channel.matrix.grouped) Is that the right way to express the model in (n)lme-notation? Cheers, Mikkel. ______________________________________________ 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.