[R] nlme formula from model specification

[Mikkel Meyer Andersen]

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.