R: Logical Check of a Bayesian Model

is.bayesian {LaplacesDemon} | R Documentation

## Logical Check of a Bayesian Model

### Description

This function provides a logical test of whether or not a `Model` specification function is Bayesian.

### Usage

    is.bayesian(Model, Initial.Values, Data)

### Arguments

`Model` | This is a model specification function. For more information, see the `LaplacesDemon` function.
`Initial.Values` | This is a vector of initial values, or current parameter values. For more information, see the `LaplacesDemon` function.
`Data` | This is a list of data. For more information, see the `LaplacesDemon` function.

### Details

This function tests whether or not a model is Bayesian by comparing the first two returned arguments: the logarithm of the unnormalized joint posterior density (`LP`) and deviance (`Dev`). The deviance (D) is

D = -2 LL

,

where LL is the log-likelihood. Consequently,

LL = D / -2

,

and LP is the sum of LL and prior probability densities. If LP = LL, then the model is not Bayesian, because prior densities are absent.

### Value

The `is.bayesian` function returns a logical value of `TRUE` when the model is Bayesian, and `FALSE` otherwise.

### Author(s)

Statisticat, LLC. software@bayesian-inference.com

### See Also

`LaplacesDemon`.

[Package LaplacesDemon version 16.1.1 Index]