Displaying 2 results from an estimated 2 matches for "g761".
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761
2009 Mar 18
3
Extreme AIC or BIC values in glm(), logistic regression
...ignificant, which is impossible, because
we expect some would be dropped. This situation is not uncommon.
A summary output like this:
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.883e+14 1.671e+07 29217415 <2e-16 ***
g761 -5.383e+14 9.897e+07 -5438529 <2e-16 ***
g2809 -1.945e+15 1.082e+08 -17977871 <2e-16 ***
g3106 -2.803e+15 9.351e+07 -29976674 <2e-16 ***
g4373 -9.272e+14 6.534e+07 -14190077 <2e-16...
2009 Mar 26
1
Extreme AIC in glm(), perfect separation, svm() tuning
...n,
coefficients converge. in this case, using brglm() does help! It stabilize
the AIC, and the classification power is better.
Code and output: (need to install package: brglm)
matrix <- read.table("http://ihome.ust.hk/~haitian/sample.txt")
names(matrix)<- c("g0","g761","g2809","g3106","g4373","g4583")
fo <- as.formula(g0 ~ g761 * g2809 * g3106 * g4373 * g4583)
library(MASS)
library(brglm)
lr <- brglm(formula= fo, family=binomial(link=logit), data=matrix)
summary(lr)
Coefficients:...