[R] glm stability

[Erwann.Rogard at sanofi-aventis.com]

hi all,

i have an iterative algorithm that relies on glm at each step to compute
a set of coefficients (gamma). depending on the input to the algorithm,
glm may at certain iterations generate crazy values (associated with
glm$converge = FALSE). in some cases, start = last value of gamma
resolves the problem, while in others, it causes the problem (as in the
example below).

of course i could evaluate glm with and without the start value, and
takes the first that does not fail. however, i welcome any better
suggestion.

also, i'd like to understand how the start value is internally generated
by glm (if it is ommitted from the function call glm(...) ).

thanks!

example:

y<-scan(my.fileY)
X<-scan(my.fileX)
X<-matrix(X,ncol=4)

Case 1) (converge = FALSE)

$ glm(formula = y ~ X - 1, family = binomial, start = c(-0.734,
-1.79, 4.34, 7.79)) 

Coefficients:
        X1          X2          X3          X4  
-4.020e+13  -1.593e+14  -1.150e+14  -4.348e+14  

Case 2) (converge = TRUE)


$ glm(y~X-1,family=binomial)

Call:  glm(formula = y ~ X - 1, family = binomial) 

Coefficients:
     X1       X2       X3       X4  
-0.1551  -1.1596   0.7605   1.6463  




my.fileX

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