
Linear model without interaction terms
 
Linear model with interaction terms



d_{
max
}= 2

d_{
max
}= 3

d_{
max
}= 4

d_{
max
}= 5
 
d_{
max
}= 2

d_{
max
}= 3

d_{
max
}= 4

d_{
max
}= 5


p=30

0.1

1.1

8.7

9.5
 
0.4

4.7

38.6

374.6

p=60

0.5

10.5

114.3

−
 
1.8

39.4

661.6

−

p=120

2.8

116.3

−

−
 
8.2

350.1

−

−

p=500

150.3

−

−

−
 
238.7

−

−

−

 Computation times (in seconds) for proposed Bayesian variable selection procedure, using empirical Bayes to select between two priors (M = 2) and to set the prior strength parameter λ (optimisation performed over ten values of λ). Results shown for varying values of d_{
max
}(maximum number of predictors allowed in a model) and p (total number of predictors), for both a linear model without interaction terms and a linear model with interaction terms. (Data and model priors generated using random numbers and results are averages over three iterations. Computation performed on a standard singlecore personal computer; 1.6GHz, 2GB RAM. ‘’ denotes a (p,d_{
max
}) regime where the procedure failed due to insufficient memory).