I'm using gl1ce with family=binomial like so:
>yy
succ fail
[1,] 76 23
[2,] 32 67
[3,] 56 43
...
[24,] 81 18>xx
c1219 c643
X1 0.04545455 0.64274145
X2 0.17723669 0.90392792
...
X24 0.80629054 0.12239320>test.gl1ce <- gl1ce(yy ~ xx, family = binomial(link=logit), bound = 0.5 )
or
>omit <- c(2,3)
>test.gl1ce <- gl1ce(yy[-omit,] ~ xx[-omit,], family = binomial(link=logit), bound = 1 )
this seems to work fine and as i change the shrinkage parameter everything behaves as expected.
if i try to get the fitted values (y-hat) using predict i have no problems:
> predict.gl1ce(test.gl1ce)
[1] 0.38129977 0.16513661 0.47666779 0.45348757 0.09916513 0.18167674
[7] 0.11047684 0.15786664 0.14765670 0.40657031 0.19072570 0.80259477
[13] 0.36317090 0.35930557 0.23700520 0.17579282 0.18835043 0.52306049
[19] 0.28388953 0.41262864 0.29933710 0.43556139 0.15276727 0.73017401
***
I have problems, however, when i try to use predict.gl1ce() with newdata.
so, the following tries all give errors:
> predict.gl1ce(test.gl1ce, xx, family=binomial(link-logit))
> predict.gl1ce(test.gl1ce, xx)
> predict.gl1ce(test.gl1ce, xx[omit,], family=binomial(link-logit))
Error in predict.l1ce(test.gl1ce, xx, family = binomial(link - logit)) :
Argument `newdata' is not a data frame, and cannot be coerced to an appropriate model matrix
the following weak try also bombs: > predict.gl1ce(test.gl1ce, data.frame(xx), family=binomial(link-logit)) Error in eval(expr, envir, enclos) : attempt to apply non-function
I've tried quite a few variations. It seems I'm missing something, but if glm or gl1ce take a certain
data format then the corresponding predict me,thods should (what am i missing).
thanks, Rico
Richard Bonneau Institute for Systems Biology Seattle, WA 206-732-1463 206-732-1299 (fax)
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