calculateMarginalLogLikelihood {AnaCoDa} R Documentation

## Calculates the marginal log-likelihood for a set of parameters

### Description

initializes the model object.

### Usage

```calculateMarginalLogLikelihood(
parameter,
mcmc,
mixture,
n.samples,
divisor,
warnings = TRUE
)
```

### Arguments

 `parameter` An object created with `initializeParameterObject`. `mcmc` An object created with `initializeMCMCObject` `mixture` determines for which mixture the marginal log-likelihood should be calculated `n.samples` How many samples should be used for the calculation `divisor` A value > 1 in order to scale down the tails of the importance distribution `warnings` Print warnings such as when the variance of a parameter is 0, which might occur when parameter is fixed

### Details

calculateMarginalLogLikelihood Calculate marginal log-likelihood for calculation of the Bayes factor using a generalized harmonix mean estimator of the marginal likelihood. See Gronau et al. (2017) for details

### Value

This function returns the model object created.

### Examples

```## Not run:
# Calculate the log-marginal likelihood
parameter <- loadParameterObject("parameter.Rda")
mcmc <- loadMCMCObject("mcmc.Rda")
calculate_marginal_likelihood(parameter, mcmc, mixture = 1,
samples = 500, scaling = 1.5)

# Calculate the Bayes factor for two models
parameter1 <- loadParameterObject("parameter1.Rda")
parameter2 <- loadParameterObject("parameter2.Rda")
mcmc1 <- loadMCMCObject("mcmc1.Rda")
mcmc2 <- loadMCMCObject("mcmc2.Rda")
mll1 <- calculate_marginal_likelihood(parameter1, mcmc1, mixture = 1,
samples = 500, scaling = 1.5)
mll2 <- calculate_marginal_likelihood(parameter2, mcmc2, mixture = 1,
samples = 500, scaling = 1.5)
cat("Bayes factor: ", mll1 - mll2, "\n")

## End(Not run)

```

[Package AnaCoDa version 0.1.4.4 Index]