# Maximum Likelihood Estimation (MLE) with optimizer

`SimpleMC`

through the `MaxLikeAnalyzer class`

uses the L-BFGS-B algorithm from `scipy.optimize.minimize`

and tries to maximize the Likelihood function based on a cosmological model and selected datasets. It then obtains the errors of the Hessian.

An example of `ini file`

to use the `MaxLikeAnalyzer class`

is as follows:

```
[custom]
...
model = LCDM
datasets = SN+HD
analyzer = maxlike
...
[maxlike]
;compute errror from Hessian matrix
;False/True
compute_errors = True
;If withErrors is True
;plot Fisher matrix
show_contours = True
;If showplot is True, then
;2D plot for the parameters:
plot_par1 = h
plot_par2 = Om
;[DerivedParameters]
compute_derived = True
```

Lastly, we can run `SimpleMC`

as in the example Python script using the `ini file`

with the `maxlike`

information.

## Notebook example

In the following notebook there is an example of the use of `ga_deap`

and `maxlike`

.