multinomRob - error message

Hi,

I would like to use the multinomRob function to test election results.  
However, depending on which independent variables I include and how  
many categories I have in the dependent variable, the model cannot be  
estimated.

My data look like this (there are 68 observations):

head(database)

RESTE09 GAUCHE09 PDC09 PLR09 UDC09 MCG09    RESTE05  GAUCHE05      PDC05
D1    1455     5931  4726  7283  3611  5179 0.04487642 0.1707559 0.27561790
D2    1736    10548  6905 27660  5430  5360 0.04487109 0.1797425 0.13782229
D3    4208    12452  1721  8210  3179  8960 0.18580836 0.3218897 0.05659316
D4    2182     9208  7288 10654  2951  5205 0.08227831 0.2591124 0.19605699
D5    6129    13909 12691 15560  3129 12551 0.10438878 0.2362780 0.23772964
D6    3027    13517  4702 17899  5299  5758 0.10507522 0.2034102 0.07564233
        PLR05      UDC05      MCG05       dim1        dim2        dim3
D1 0.3006495 0.08555836 0.12254194  0.4327918 -0.37563170  0.23139759
D2 0.4879385 0.09903729 0.05058832  1.2723817  0.03128996 -0.10629471
D3 0.2296300 0.07822276 0.12785602 -0.8002237 -0.12194377  0.18147181
D4 0.3051325 0.06789533 0.08952449  0.4321835  0.11445829  0.24636903
D5 0.2811336 0.06624300 0.07422700  0.2560408  0.07019505  0.05611872
D6 0.4186317 0.10281440 0.09442613  0.4487914 -0.15539599 -0.04779844



I defined the model as follows:

mnr<-multinomRob(list(

+ GAUCHE09~GAUCHE05+dim1+dim2+dim3,
+ PDC09~PDC05+dim1+dim2+dim3,
+ PLR09~PLR05+dim1+dim2+dim3,
+ UDC09~UDC05+dim1+dim2+dim3,
+ MCG09~MCG05+dim1+dim2+dim3,
+ RESTE09~0),database,print.level=0)


And the error message is:

Error in multinomT.foo$se$beta : $ operator is invalid for atomic vectors
In addition: There were 11 warnings (use warnings() to see them)

warnings()

Warning messages:
1: In optim(param, fn = mt.dev, method = method, control = control,  ... :
   unknown names in control: tol
2: In fn(par, ...) : value out of range in 'lgamma'
3: In fn(par, ...) : value out of range in 'lgamma'
4: In fn(par, ...) : value out of range in 'lgamma'
5: In fn(par, ...) : value out of range in 'lgamma'
6: In fn(par, ...) : value out of range in 'lgamma'
7: In fn(par, ...) : value out of range in 'lgamma'
8: In fn(par, ...) : value out of range in 'lgamma'
9: In fn(par, ...) : value out of range in 'lgamma'
10: In fn(par, ...) : value out of range in 'lgamma'
11: In fn(par, ...) : value out of range in 'lgamma'


Is my model uncorrectly defined?

many thanks,

danielle martin
graduate student
department of political science
university of michigan