[R] nlme formula from model specification

[ONKELINX, Thierry]

Dear Mikkel,

You need to do some reading on terminology.

In your model the fixed effects are channel 1, 2 and 3. samplenumber is
a random effect and the error term is an error term

The model you described has the notation below. You do not need to
create the grouped data structure.

lme(channel0 ~ pos + samplenumber + channel1 + channel2 + channel3,
   random = ~ 1 | samplenumber,
   correlation = corAR1(value = 0.5, form = ~ pos | samplenumber),
   data = channel.matrix) 

HTH,

Thierry

PS There is a dedicated mailing list for mixed models:
R-sig-mixed-models

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen
Belgium

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium

tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be
www.inbo.be

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than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

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ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey
  

> -----Oorspronkelijk bericht-----
> Van: r-help-bounces op r-project.org 
> [mailto:r-help-bounces op r-project.org] Namens Mikkel Meyer Andersen
> Verzonden: donderdag 2 september 2010 13:30
> Aan: r-help op r-project.org
> Onderwerp: [R] nlme formula from model specification
> 
> 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.
> 
> ______________________________________________
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> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 

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