marginal.lkl.nl {BMAmevt} R Documentation

## Marginal likelihoods of the PB and NL models.

### Description

Wrappers for `marginal.lkl`, in the specific cases of the PB and NL models, with parameter `likelihood` set to `dpairbeta` or `dnestlog`, and `prior` set to `prior.pb` or `prior.nl`. See `MCpriorIntFun` for more details.

### Usage

```marginal.lkl.nl(
dat,
Nsim = 10000,
displ = TRUE,
Hpar = get("nl.Hpar"),
Nsim.min = Nsim,
precision = 0,
show.progress = floor(seq(1, Nsim, length.out = 20))
)

marginal.lkl.pb(
dat,
Nsim = 10000,
displ = TRUE,
Hpar = get("pb.Hpar"),
Nsim.min = Nsim,
precision = 0,
show.progress = floor(seq(1, Nsim, length.out = 20))
)
```

### Arguments

 `dat` The angular data set relative to which the marginal model likelihood is to be computed `Nsim` Total number of iterations to perform. `displ` logical. If `TRUE`, a plot is produced, showing the temporal evolution of the cumulative mean, with approximate confidence intervals of +/-2 estimated standard errors. `Hpar` A list containing Hyper-parameters to be passed to `prior`. `Nsim.min` The minimum number of iterations to be performed. `precision` the desired relative precision. See `MCpriorIntFun`. `show.progress` An vector of integers containing the times (iteration numbers) at which a message showing progression will be printed on the standard output.

### Value

The list returned by `marginal.lkl`, i.e., the one returned by `MCpriorIntFun`

### See Also

`marginal.lkl`, `MCpriorIntFun` .

### Examples

```## Not run:

marginal.lkl.pb(dat=Leeds ,
Nsim=20e+3 ,
displ=TRUE, Hpar = get("pb.Hpar") ,
)

marginal.lkl.nl(dat=Leeds ,
Nsim=10e+3 ,
displ=TRUE, Hpar = get("nl.Hpar") ,
)

## End(Not run)
```

[Package BMAmevt version 1.0.4 Index]