# MVNORM

##### Create Samples for BAMLSS by Multivariate Normal Approximation

This sampler function for BAMLSS uses estimated `parameters`

and the Hessian
information to create samples from a multivariate normal distribution. Note that smoothing
variance uncertainty is not accounted for, therefore, the resulting credible intervals
are most likely too narrow.

- Keywords
- regression

##### Usage

```
MVNORM(x, y = NULL, family = NULL, start = NULL,
n.samples = 500, hessian = NULL, ...)
```

##### Arguments

- x
The

`x`

list, as returned from function`bamlss.frame`

, holding all model matrices and other information that is used for fitting the model. Or an object returned from function`bamlss`

.- y
The model response, as returned from function

`bamlss.frame`

.- family
A bamlss family object, see

`family.bamlss`

.- start
A named numeric vector containing possible starting values, the names are based on function

`parameters`

.- n.samples
Sets the number of samples that should be generated.

- hessian
The Hessian matrix that should be used. Note that the row and column names must be the same as the names of the

`parameters`

. If`hessian = NULL`

the function uses`optim`

to compute the Hessian if it is not provided within`x`

.- …
Arguments passed to function

`optim`

.

##### Value

Function `MVNORM()`

returns samples of parameters. The samples are provided as a
`mcmc`

matrix.

##### See Also

`bamlss`

, `bamlss.frame`

,
`bamlss.engine.setup`

, `set.starting.values`

, `bfit`

,
`GMCMC`

##### Examples

```
# NOT RUN {
## Simulated data example illustrating
## how to call the sampler function.
## This is done internally within
## the setup of function bamlss().
d <- GAMart()
f <- num ~ s(x1, bs = "ps")
bf <- bamlss.frame(f, data = d, family = "gaussian")
## First, find starting values with optimizer.
o <- with(bf, bfit(x, y, family))
## Sample.
samps <- with(bf, MVNORM(x, y, family, start = o$parameters))
plot(samps)
# }
```

*Documentation reproduced from package bamlss, version 1.1-2, License: GPL-2 | GPL-3*