### using airemlf90

# Example 1: with intercept
DATAFILE
test.dat
NUMBER_OF_TRAITS
1
NUMBER_OF_EFFECTS
9
OBSERVATION(S)
3
WEIGHT(S)
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT [EFFECT NESTED]
1 2 cross
6 1 cov
7 1 cov
5 5 cross
6 5 cov 5
7 5 cov 5
5 10 cross
6 10 cov 5
7 10 cov 5
RANDOM_RESIDUAL VALUES
10
RANDOM_GROUP
4 5 6
RANDOM_TYPE
diagonal
FILE

(CO)VARIANCES
1 0.1 0.1
0.1 1 0.1
0.1 0.1 1
RANDOM_GROUP
7 8 9
RANDOM_TYPE
add_animal
FILE
animal.ped
(CO)VARIANCES
1 0.1 0.1
0.1 1 0.1
0.1 0.1 1
OPTION hetres_pos 6 7
OPTION hetres_pol 4.0 1.0 0.1

### using airemlf90

# Example 2: with no intercept
DATAFILE
test.dat
NUMBER_OF_TRAITS
1
NUMBER_OF_EFFECTS
7
OBSERVATION(S)
3
WEIGHT(S)
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT [EFFECT NESTED]
1 2 cross
6 1 cov
7 1 cov
6 5 cov 5
7 5 cov 5
6 10 cov 5
7 10 cov 5
RANDOM_RESIDUAL VALUES
10
RANDOM_GROUP
4 5
RANDOM_TYPE
diagonal
FILE

(CO)VARIANCES
1 0.1
0.1 1
RANDOM_GROUP
6 7
RANDOM_TYPE
add_animal
FILE
animal.ped
(CO)VARIANCES
1 0.1
0.1 1
OPTION hetres_pos 6 7
OPTION hetres_pol 1.0 0.1

### using gibbs3f90

DATAFILE
test.dat
NUMBER_OF_TRAITS
1
NUMBER_OF_EFFECTS
9
OBSERVATION(S)
3
WEIGHT(S)
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT [EFFECT NESTED]
1 2 cross
6 1 cov
7 1 cov
5 5 cross
6 5 cov 5
7 5 cov 5
5 10 cross
6 10 cov 5
7 10 cov 5
RANDOM_RESIDUAL VALUES
10
RANDOM_GROUP
4 5 6
RANDOM_TYPE
diagonal
FILE

(CO)VARIANCES
1 0.1 0.1
0.1 1 0.1
0.1 0.1 1
RANDOM_GROUP
7 8 9
RANDOM_TYPE
add_animal
FILE
animal.ped
(CO)VARIANCES
1 0.1 0.1
0.1 1 0.1
0.1 0.1 1
OPTION hetres_int 8 5