R: Evaluates a Monte-Carlo model

evalmcmod {mc2d} | R Documentation

## Evaluates a Monte-Carlo model

### Description

Evaluates a `mcmodel` object (or a valid expression) using a specified number of simulations and with (or without) a specified seed.

### Usage

    evalmcmod(expr, nsv=ndvar(), nsu=ndunc(), seed=NULL)

### Arguments

`expr` | A model of class `mcmodel` or a valid expression.
`nsv` | The number of simulations in the dimension of variability used in the evaluation.
`nsu` | The number of simulations in the dimension of uncertainty used in the evaluation.
`seed` | The random seed used for the evaluation. If NULL the seed is unchanged.

### Details

The model is evaluated. The intermediate variables used to build the mc object are not stored.

### Value

The results of the evaluation. It should be a mc object.

### Note

The seed is set at the beginning of the evaluation. Thus, the complete similarity of two evaluations with similar seed is not certain, depending on the structure of your model.

### See Also

`mcmodel`

`evalmccut` to evaluate high dimension Monte Carlo Model in a loop.

### Examples

    data(ec)
    ec$modEC1
    evalmcmod(ec$modEC1, nsv=100, nsu=100, seed=666)

[Package mc2d version 0.1-18 Index]