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Prediction uncertainty can be explored by declaring any predicted quantities of interest as sdreport variables in the PARAMETER section. Their
estimated standard deviations and correlations will then be computed and
reported in the .std and .cor output files.
The standard error is automatically calculated and reported for all parameters declared with init (e.g., a and b). To generate a standard error
report for a derived variable (in our example, the derived variable would
be the estimated weight of algae, pred y), declare the quantity of interest
(pred y) as a sdreport vector in the parameter section:
The standard deviation information will be reported in the *.std and
*.cor files. The first few lines of the simplematrix.std error report generated
by the above example are:
index
1
2
3
4
5
...
name
a
b
pred y
pred y
pred y
value
4.0782e+000
1.9091e+000
2.1691e+000
4.0782e+000
5.9873e+000
std dev
3.5248e-001
7.7850e-002
4.1560e-001
3.5248e-001
2.9644e-001
The first few lines of the .cor report are:
The logarithm of the determinant of the hessian = 8.10168
index
name
value
std dev
1
2
3
1
a
4.0782e+000 3.5248e-001
1.0000
2
b
1.9091e+000 7.7850e-002 -0.7730 1.0000
3
pred_y 2.1691e+000 4.1560e-001
0.9929 -0.8429 1.0000
4
pred_y 4.0782e+000 3.5248e-001
1.0000 -0.7730 0.9929
...
56
4
1.0000