The
**brnn** package was developed by Paulino Perez Rodriguez and Daniel Gianola, and it implements the two-layer Bayesian regularized neural network described in the previous section. The main function in the package is `brnn( )`

that can be called using the following command:

>brnn(x,y,neurons,normalize,epochs,…,Monte_Carlo,…)

Here, *x* is an *n x p* matrix where *n* is the number of data points and *p* is the number of variables; *y* is an *n* dimensional vector containing target values. The number of neurons in the hidden layer of the network can be specified by the variable `neurons`

. If the indicator function `normalize`

is `TRUE`

, it will normalize the input and output, which is the default option. The maximum number of iterations during model ...

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