Simulate SimBiology model, adding variations by sampling error model

```
[ynew,parameterEstimates]
= random(resultsObj)
```

[ynew,parameterEstimates]
= random(resultsObj,data,dosing)

`[`

returns simulation
results `ynew`

,`parameterEstimates`

]
= random(`resultsObj`

)`ynew`

with added noise using the error
model information specified by the `resultsObj.ErrorModelInfo`

property
and estimated parameter values `parameterEstimates`

.

`[`

uses
the specified `ynew`

,`parameterEstimates`

]
= random(`resultsObj`

,`data`

,`dosing`

)`data`

and `dosing`

information.

The noise is only added to states that are responses which are
the states included in the `responseMap`

input argument
when you called `sbiofit`

. If
there is a separate error model for each response, the noise is added
to each response separately using the corresponding error model.

[1] Yi, T-M., Kitano, H., and Simon, M. (2003). A quantitative characterization of the yeast heterotrimeric G protein cycle. PNAS. 100, 10764–10769.