Parent Command
>> ERROR
Subcommand

Description
The estimated error variance s_{0}^{2} represents the variance of the mean weighted
residual and is thus a measure of goodnessoffit:
The value s_{0}^{2} is used in the subsequent error analysis. For example, the
covariance matrix of the estimated parameters, C_{pp}, is directly proportional
to the scalar s_{0}^{2}. Note that if the residuals are consistent with the
distributional assumption about the measurement errors (i.e., matrix C_{zz}),
then the estimated error variance assumes a value close to one. s_{0}^{2} is also an
estimate for the true or a priori error variance sigma_{0}^{2}.
It can be shown that the ratio (s_{0}^{2}/sigma_{0}^{2}) follows an Fdistribution with
the two degrees of freedom f_{1}=mn, and f_{2}=infinity. Therefore, it can be
statistically tested to see whether the final match deviates significantly
from the modeler's expectations, expressed by matrix C_{zz}.
This is called the Fisher Model Test. The user must decide
whether the error analysis should be based on the a posteriori or a priori
error variance (see commands
Fisher Model Test  Error Variance  Comment 

error either in the functional or stochastic model  
model test passed  
probably error in stochastic model 
Example
> COMPUTATION
>> ERROR
>>> let the FISHER model test decide whether the
a priori or a posteriori error variance should be used
>>> confidence level 1ALPHA : 95 %
<<<
See Also