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Table 1 Preferences of Model Selection Criteria on Real Data

From: Thinking outside the curve, part I: modeling birthweight distribution

Number of Components FLIC
5000
BIC
5000
AIC
5000
FLIC
10000
BIC
10000
AIC
10000
1 0 0 0 0 0 0
2 20 21 1 8 11 0
3 5 4 4 5 5 0
4 0 0 14 12 9 15
5 0 0 1 0 0 1
6 0 0 4 0 0 8
7 0 0 1 0 0 1
Number of Components FLIC
25000
BIC
25000
AIC
25000
FLIC
50000
BIC
50000
AIC
50000
1 0 0 0 0 0 0
2 0 0 0 0 0 0
3 0 0 0 0 0 0
4 25 25 5 22 22 1
5 0 0 1 0 0 0
6 0 0 10 3 3 6
7 0 0 9 0 0 18
  1. The columns "FLIC 5000", "BIC 5000", and "AIC 5000" contain the preferences of the three model selection criteria for the number of components in a normal mixture model for birthweight distribution, based on 25 samples of size 5000 from the population of white singletons born to heavily smoking mothers. The next nine columns correspond to sample sizes of 10000, 25000, and 50000.