## risk.GaussianCopula


The Gaussian copula with correlation matrix `correlation`.


Usage


``` python
risk.GaussianCopula()
```


## Parameters


`correlation: list of list of float`  
Symmetric, unit diagonal, positive definite.


## Raises


`ValueError`  
If the matrix is not a valid correlation matrix.


## Examples

``` python
>>> from prospicio.risk import GaussianCopula
>>> c = GaussianCopula([[1.0, 0.5], [0.5, 1.0]])
>>> u = c.sample(3, seed=1)
>>> len(u), all(0.0 < x < 1.0 for row in u for x in row)
```

(3, True)


## Attributes

| Name | Description |
|----|----|
| [dim](#dim) | Number of dimensions. |

------------------------------------------------------------------------


#### dim


Number of dimensions.


`dim: int`


## Methods

| Name | Description |
|----|----|
| [sample()](#sample) | [n](distributions.Binomial.md#prospicio.distributions.Binomial.n) draws of uniforms; draw `i` uses stream `i` of [seed](aggregate.EventSet.md#prospicio.aggregate.EventSet.seed). |

------------------------------------------------------------------------


#### sample()


[n](distributions.Binomial.md#prospicio.distributions.Binomial.n) draws of uniforms; draw `i` uses stream `i` of [seed](aggregate.EventSet.md#prospicio.aggregate.EventSet.seed).


Usage


``` python
sample(n, seed)
```


##### Parameters


`n: int`  

`seed: int`  


##### Returns


`list of list of float`