Table 2

Cross-validations of the EBLASSO-NE, EBLASSO-NEG and LASSO for the simulation with only main effects
Algorithm Parametersa logL ± STEb
0.0011 −0.39 ± 0.03
0.0022 −0.42 ± 0.03
0.0447 −0.42 ± 0.04
EBLASSO-NE 0.0500 −0.36 ± 0.02c
0.0631 −0.39 ± 0.02
0.1259 −0.41 ± 0.03
0.2512 −0.40 ± 0.01
(−0.5,0.05) −0.38 ± 0.03
(0.01,0.05) −0.37 ± 0.02
(1,0.05) −0.47 ± 0.02
EBLASSO-NEG (0.01,5) −0.39 ± 0.03
(0.01,6) –0.36 ± 0.02c
(0.01,7) −0.37 ± 0.02
0.1037 −0.56 ± 0.02
0.0516 −0.44 ± 0.03
LASSO 0.0257 −0.37 ± 0.04
0.0128 −0.35 ± 0.05c
0.0064 −0.36 ± 0.06

aParameters are λ for EBLASSO-NE and LASSO, (a, b) for EBLASSO-NEG.

bThe average log likelihood and standard error were obtained from ten-fold cross validation.

cThe optimal log likelihood and corresponding parameter(s) chosen for comparison with other methods.

Huang et al.

Huang et al. BMC Genetics 2013 14:5   doi:10.1186/1471-2156-14-5

Open Data