Avec Glim4:
glim
$pag on !pour avoir la pagination
$echo on !pour avoir le detail des fichiers importes
$uni 8$
$dat x f y$
$din pois33$
0.1 1 2
0.5 1 4
1 1 3
2 1 8
0.5 2 4
1.5 2 9
2.5 2 6
4 2 16
$fac f 2$
$yva y$
$err p$
$li i$
$fit f*x$
scaled deviance = 3.3844 at cycle 3
residual df = 4
$loo %x2$
3.155
$fit -f.x$
scaled deviance = 3.3870 (change = +0.002543) at cycle 3
residual df = 5 (change = +1 )
$loo %x2$
3.161
$fit -f$
scaled deviance = 3.7234 (change = +0.3364) at cycle 3
residual df = 6 (change = +1 )
$loo %x2$
3.532
$dis a$
estimate s.e. parameter
1 1.926 1.073 1
2 3.024 0.8049 X
scale parameter 1.000
$dis r$
unit observed fitted residual
1 2 2.228 -0.153
2 4 3.438 0.303
3 3 4.950 -0.876
4 8 7.974 0.009
5 4 3.438 0.303
6 9 6.462 0.998
7 6 9.486 -1.132
8 16 14.023 0.528
$plo %fv %yv '*'$
| *
|
12.5 +
|
|
10.0 +
| *
| *
7.5 +
| *
|
5.0 + *
|
| 2
2.5 + *
|
+--------+--------+--------+--------+--------+--------+----
0.0 2.5 5.0 7.5 10.0 12.5 15.0
$plo %fv %rs '*'$
| *
|
12.5 +
|
|
10.0 +
| *
| *
7.5 +
| *
|
5.0 + *
|
| 2
2.5 + *
|
+-----------+-----------+-----------+-----------+-----------+
-1.5 -1.0 -0.5 0.0 0.5 1.0
$extract %di$
$loo %di$
%DI
1 0.02422288
2 0.08725201
3 0.89540601
4 0.00008261
5 0.08725201
6 0.88698816
7 1.47563529
8 0.26652852
$dis c$
correlations between parameter estimates
1 1.0000
2 -0.6970 1.0000
1 2
$dis v$
(co)variance matrix of parameter estimates
1 1.151
2 -0.6019 0.6479
1 2
$stop