sourceR (version 0.2.0)

subset_posterior: Subsets the posterior of the McMC posterior from saBayes output.

Description

Subsets the posterior of the McMC posterior from saBayes output by parameter, time, location, type, source and iteration number.

Usage

subset_posterior(object, params, t, l, i, j, iters)

Arguments

object

an object that inherits from class source_attribution, such as a source_attribution object produced using saBayes.

params

A vector containing the names of the parameters to be returned. Default is all.

t

A vector containing the names of the times to be returned. Default is all.

l

A vector containing the names of the locations to be returned. Default is all.

i

A vector containing the names of the types to be returned. Default is all.

j

A vector containing the names of the sources to be returned. Default is all.

iters

A vector containing the iterations to be returned.

Value

Returns the subsetted posterior in the same format as the input object. This can be passed to summary.source_attribution or flatten in the same way the full posterior can be.

See Also

saBayes, flatten, summary

Examples

##########################################################################
## Access simulated data set #############################################
##########################################################################
data(sim_SA)

##########################################################################
## Set priors ############################################################
##########################################################################

priors <- list(a = 1, r = 1, theta = c(0.01, 0.00001))

##########################################################################
## Run model #############################################################
##########################################################################

res <- saBayes(formula = Human~Source1+Source2+Source3+Source4+Source5, 
               time=~Time, location=~Location, type=~Type,
               data=sim_SA$data, priors = priors,
               alpha_conc = 1, prev = sim_SA$prev,
               likelihood_dist = "pois", n_iter = 20)
               
##########################################################################
#### Subset ##############################################################
##########################################################################

subset_res <- subset_posterior(res, params = c("a", "li", "lj"), 
                               t = "1", l = "B", j = c("Source2", "Source1"), 
                              i = c("47", "10"), iters = c(3:10))
flat_res <- flatten(subset_res)
str(subset_res)