**Syntax**

` >>> POSTERIORI`

**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 goodness-of-fit:

The a posteriori error variance s_{0}^{2} or a priori error variance sigma_{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} or sigma_{0}^{2}, respectively. 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. The user must decide whether the error analysis should be based on the a posteriori or a priori error variance. The decision can also be delegated to the Fisher Model Test (see command `>>> FISHER).` iTOUGH2 uses the a posteriori error variance s_{0}^{2} by default.

**Example**

` > COMPUTATION
>> ERROR analysis
>>> based on A POSTERIORI error variance
<<<`

**See Also**

` >>> FISHER | >>> PRIORI
`