Dear Users,
In case of ridge logistic regression, i want to calculate the optimum
penalty using aic and bic criteria. Here is the sample code:
fit <- lrm(RES ~CAT01+NUM01+NUM02+CAT02+CAT03+CAT04+NUM03+CAT05+CAT06+NUM04+
CAT07+CAT08+NUM05+NUM06, data = train.data, x = TRUE, y = TRUE)
pentrace(fit, penalty = list(seq(.001, 5, by=.1)))
output:
Best penalty:
penalty df
1.001 13.26012
Var1 df aic bic aic.c
1 0.001 13.99894 337.7431 279.2273 336.8458
2 0.101 13.89814 337.9293 279.8348 337.0446
3 0.201 13.80665 338.0721 280.3600 337.1988
4 0.301 13.72260 338.1815 280.8208 337.3186
5 0.401 13.64461 338.2646 281.2299 337.4114
6 0.501 13.57167 338.3268 281.5970 337.4824
7 0.601 13.50297 338.3718 281.9292 337.5358
8 0.701 13.43791 338.4027 282.2320 337.5746
9 0.801 13.37600 338.4218 282.5099 337.6011
10 0.901 13.31685 338.4309 282.7663 337.6173
11 1.001 13.26012 338.4316 283.0040 337.6248
12 1.101 13.20556 338.4249 283.2254 337.6246
13 1.201 13.15295 338.4119 283.4323 337.6178
14 1.301 13.10208 338.3933 283.6264 337.6053
15 1.401 13.05282 338.3699 283.8090 337.5876
16 1.501 13.00501 338.3422 283.9811 337.5655
17 1.601 12.95854 338.3107 284.1438 337.5394
...
...
I can't understand what does it mean by 'best penalty'. The aic and bic
values corresponding to the best penalty are not minimum. Please clarify.
Tirtha
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