data.raw	!  dataset
1000					! iterations 
100					! burnin 
10						! step 
5000		   	        ! number of individuals 
23					! number of variables  
1					! number of probits 
5					! number of linear equations 
	! FACTORS  
F 2					! Problems, Where
1					! Number of Factors
	! Factors 
F					! Restrict factor to be normal? 
2					! Mixture elements for factor 
T					! Make the mean of the factor zero? 
F					! Make the first scale equal to 1 
F					! Scale mixture only? (restrict all means to zero) 
F					! Mean mixture only? (restrict all scales to 1) 
factor.out				! output path 
	! PROBIT (Train Year 1)
14 					!location of outcome
T 23					! Indicator for Missings, Location
2					! number of X's
22 4 ! location of X's in dataset
F 5					! Drop variables predict perfectly? Location
F					! Normalizations In loadings
training.out				! output path 
F 5000				! Use previous run as initial value, iteration
	! Y1
18 					!location of outcome
T 19					! Indicator for Missings
2  ! number of X's
22 2 ! location of X's in dataset
F					! Normalizations In loadings
Y1.out				! output path 
F 5000				! Use previous run as initial value, iteration
	! Y0
20 					!location of outcome
T 21					! Indicator for Missings
2  ! number of X's
22 2 ! location of X's in dataset
F					! Normalizations In loadings
Y0.out				! output path 
F 5000				! Use previous run as initial value, iteration
	! TEST I
11 					!location of outcome
T 23					! Indicator for Missings
2  ! number of X's
22 3 ! location of X's in dataset
F					! Normalizations In loadings
test1.out				! output path 
F 5000				! Use previous run as initial value, iteration
	! TEST I
12 					!location of outcome
T 23					! Indicator for Missings
2  ! number of X's
22 3 ! location of X's in dataset
F					! Normalizations In loadings
test2.out				! output path 
F 5000				! Use previous run as initial value, iteration
	! TEST I
13 					!location of outcome
T 23					! Indicator for Missings
2  ! number of X's
22 3 ! location of X's in dataset
T					! Normalizations In loadings
1.0 !
1.0 !
test3.out				! output path 
F 5000				! Use previous run as initial value, iteration
 	! Precision 
0.1					! prior precision for all loadings (i.e. P(a)~N(0,thisnumber))
	! Precision for slopes 
0.1					! prior precision for all loadings (i.e. P(b)~N(0,thisnumber))



