BMMmodel {bayesmix}R Documentation

Creates text for .bug-file and data for -inits.R and -data.R-file

Description

Creates the text for the BUGS-model specification and the values of the initialization, prior specification and the observations read in by jags.

Usage

BMMmodel(y, k, priors, inits = "initsFS", aprioriWeights = 1,
         no.empty.classes = FALSE, restrict = "none", ...)

Arguments

y a numeric vector.
k integer indicating the number of segments.
priors specification of priors by a named list or a BMMpriors object.
inits specification of initial values by a named list or string indicating the function to be called.
aprioriWeights specification of prior of the a-priori weights. If aprioriWeights does not have length = k, there is an equal prior for the a-priori weights assumed.
no.empty.classes logical: should it be prevented that empty classes arise during sampling.
restrict one of "none", "mu", "tau".
... further parameters for the function specified in inits.

Details

By default the function initsFS is called for generating initial values. Any other function specified by inits is assumed to have at least x, k and restrict as input parameters.

The parameter restrict indicates if a location-shift model ("tau"), a scale contaminated model ("mu") or a model where both variables vary over components shall be fitted.

If the logical no.empty.classes is TRUE there are observations added to the model that the classes are not empty. This signifies that the likelihood when sampling the class affiliations is changed thus that any data point which is sampled and is the last one in its class stays there.

Value

If y is specified there is an object of class BMMmodel returned with components:

inits named list for -inits.R-file.
data named list for -data.R-file.
bugs text for .bug-file with prefix missing.


If y is missing there is an object of class BMMsetup returned containing the parameter specifications. When JAGSsetup is called with this object as model argument, BMMmodel is called with y and the other parameters as input arguments before creating the input files for jags.

Author(s)

Bettina Gruen

See Also

JAGSrun, initsFS

Examples

data(fish)
model <- BMMmodel(fish, k = 4, priors = list(kind = "independence",
                  parameter = "priorsFish", hierarchical = "tau"),
                  initialValues = list(S0 = 2))
model

[Package bayesmix version 0.6-0 Index]