Hi

see inline

> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Lara Reichmann
> Sent: Wednesday, December 05, 2012 1:53 AM
> To: r-h...@lists.r-project.org
> Subject: [R] nlme starting values are not the correct length
> 
> Dear R community,
> 
> I am trying to fit an nlme model where I want to estimate the fixed
> effects of two treatments on the parameters on the following equation
> Photo~(a*(1-exp(-c*PARi/a)))-b I was able to fit a simple model without
> covariates following the method described in Mixed-Effects Methods and
> Classes for S and S-PLUS, version 3.0, but when I add the covariates, I
> get the error " starting values for the fixed component are not the
> correct length"
> 
> My data has the following structure "Subject" "Species" "Fert" "Photo"
> "PARi" , where several "Photo" measurements where taken on the same
> subject by changing "PARi", 4 Species levels and 2 Fert levels, there
> are 31 Subjects (one missing value), and 323 observations
> 
> DATA extract
> 
> Subject       Species Fert    Photo   PARi
> 1     bb      1       22.5389 1499.3307
> 1     bb      1       21.881  1248.913
> 1     bb      1       21.2862 999.3387
> 1     bb      1       20.5836 799.9308
> 1     bb      1       19.3758 601.1412
> 1     bb      1       15.5915 399.815
> 1     bb      1       8.7978  200.1087
> 1     bb      1       4.4347  99.686
> 1     bb      1       2.0387  49.7842
> 1     bb      1       -1.4854 0.0576
> 2     sw      0       6.782   1500.5337
> 2     sw      0       7.1432  1249.2749
> 2     sw      0       7.3319  1000.9891
> 2     sw      0       7.5848  799.1752
> 2     sw      0       7.1882  599.5544
> 2     sw      0       6.809   399.988
> 2     sw      0       5.3877  198.7574
> 2     sw      0       3.5104  100.7115
> 2     sw      0       0.8856  50.7015
> 2     sw      0       -1.121  0.0569
> 3     jg      1       16.0827 2000.4941
> 3     jg      1       16.0236 1501.1957
> 3     jg      1       16.3818 1248.9551
> 3     jg      1       16.7815 1499.6414
> 3     jg      1       17.175  2000.6851
> 3     jg      1       16.6529 1000.2707
> 3     jg      1       15.7987 799.676
> 3     jg      1       15.5437 598.9409
> 3     jg      1       11.7683 400.7715
> 3     jg      1       4.89    200.7468
> 3     jg      1       4.1294  100.9664
> 3     jg      1       1.6008  50.9254
> 3     jg      1       -0.89   0.5347
> 4     sw      1       25.2889 2000.1454
> 4     sw      1       24.7284 1499.6191
> 4     sw      1       24.3637 1249.7523
> 4     sw      1       23.3523 1000.0944
> 4     sw      1       21.6057 800.2209
> 4     sw      1       18.8926 599.7022
> 4     sw      1       14.6598 398.9366
> 4     sw      1       7.7182  201.5697
> 4     sw      1       3.4775  100.5139
> 4     sw      1       1.169   49.7045
> 4     sw      1       -1.3558 1.6914
> 5     jg      0       6.1626  2000.9351
> 5     jg      0       7.5573  1499.6581
> 5     jg      0       7.7129  1249.5073
> 5     jg      0       7.442   1000.7276
> 5     jg      0       7.5135  799.1286
> 5     jg      0       7.1559  599.5568
> 5     jg      0       6.8161  400.3576
> 5     jg      0       4.0097  199.7442
> 5     jg      0       2.7202  101.1253
> 5     jg      0       1.0746  51.1787
> 5     jg      0       -0.5913 0.975
> 
> 
> 
> This works so far:
> 
> lightresponse<-groupedData(Photo~PARi|Subject,data=lightr,outer = ~
> Species * Fert,labels = list(x = "PAR", y = "CO2 uptake rate"),units =
> list(x = "(photon s-1)", y = "(umol/m?2 s)")) Photo.resp<-
> function(PARi,A,B,C)A*(1-exp(-C*PARi/A))-B
> Photo.resp<-deriv ((~A *(1-exp(-C*PARi/A))-
> B),c("A","B","C"),function(PARi,A,B,C){})
> 
> >
> >lightresp.fit1<-
> nlme(model=Photo~Photo.resp(PARi,A,B,C),fixed=A+B+C~1,d
> >ata=lightresponse,start=c(30,-5,0.1))#fitting  nlme without any
> >covariates
> >lightresp.fit1
> 
> OUTPUT
> > lightresp.fit1
> Nonlinear mixed-effects model fit by maximum likelihood
>   Model: Photo ~ Photo.resp(PARi, A, B, C)
>   Data: lightresponse
>   Log-likelihood: -494.5926
>   Fixed: A + B + C ~ 1
>           A           B           C
> 24.89334793  1.77983637  0.06499634
> 
> Random effects:
>  Formula: list(A ~ 1, B ~ 1, C ~ 1)
>  Level: Subject2
>  Structure: General positive-definite, Log-Cholesky parametrization
>          StdDev      Corr
> A        10.67382785 A     B
> B         0.52572012 1.000
> C         0.01433605 0.371 0.384
> Residual  0.71900020
> 
> Number of Observations: 323
> Number of Groups: 31
> 
> ##Now, I want to test the effect of Species and Fert, I don't fully
> understand how to modify the start vector, as I tried several options
> and no one seems to be correct. Do the number of levels in each factor
> matter? In that case 4 Species and 2 Fert levels, I would need 6
> initial parameters x 3? This didn't work either
> 
> >lightresp.fit2<-nlme(model=Photo~Photo.resp(PARi,A,B,C),fixed=A+B+C ~
> >Species*Fert,random=A+B+C~1,data=lightresponse,
> >start=c(24.89,0,0,0,1.78,0,0,0,0.065,0,0,0))
> Error in nlme.formula(model = Photo ~ Photo.resp(PARi, A, B, C), fixed
> = A +  :
>   starting values for the fixed component are not the correct length
> 

A aqm not an expert in nlme models but it seems that you have only three fixed 
parameters A,B,C and want to feed them with 12 starting values. This is 
probably the reason for error.

Maybe you shall also search in R-sig-mixed-models

Regards
Petr


> I hope someone out there has the answer!
> Thanks!!!
> 
> Lara
> 
> Lara G. Reichmann
> Postdoctoral Fellow
> USDA-ARS
> 808 E Blackland Rd
> Temple, TX 76502
> 
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