tfr.diagnose {bayesTFR}R Documentation

Convergence Diagnostics of TFR Markov Chain Monte Carlo

Description

Functions tfr.diagnose and tfr3.diagnose run convergence diagnostics of existing TFR MCMCs for phase II and phase III, respectively, using the raftery.diag function from the coda package. has.mcmc.converged checks if the existing diagnostics converged.

Usage

tfr.diagnose(sim.dir, thin = 80, burnin = 2000, express = FALSE, 
    country.sampling.prop = NULL, keep.thin.mcmc=FALSE, verbose = TRUE)
    
tfr3.diagnose(sim.dir, thin = 60, burnin = 10000, express = TRUE, 
    country.sampling.prop = NULL, verbose = TRUE, ...)
    
has.mcmc.converged(diag)

Arguments

sim.dir

Directory with the MCMC simulation results.

thin

Thinning interval.

burnin

Number of iterations to be discarded from the beginning of the parameter traces.

express

Logical. If TRUE, the convergence diagnostics is run only on the country-independent parameters. If FALSE, the country-specific parameters are included in the diagnostics. The number of countries can be controlled by country.sampling.prop.

country.sampling.prop

Proportion of countries that are included in the diagnostics. If it is NULL and express=FALSE, all countries are included. Setting here a number between 0 and 1, one can limit the number of countries which are then randomly sampled. Note that for long MCMCs, this argument may significantly influence the run-time of this function.

keep.thin.mcmc

Logical. If TRUE the thinned traces used for computing the diagnostics are stored on disk (see create.thinned.tfr.mcmc). It is only available for phase II MCMCs.

verbose

Logical switching log messages on and off.

diag

Object of class bayesTFR.convergence.

...

Not used.

Details

The diagnose functions invoke the tfr.raftery.diag (or tfr3.raftery.diag) function separately for country-independent parameters and for country-specific parameters. It results in two possible states: red, i.e. it did not converge, and green, i.e. it converged. The resulting object from tfr.diagnose is stored in
{sim.dir}/diagnostics/bayesTFR.convergence_{thin}_{burnin}.rda’ and can be accessed using the function get.tfr.convergence. Function tfr3.diagnose stores its result into
{sim.dir}/phaseIII/diagnostics/bayesTFR.convergence_{thin}_{burnin}.rda’ which can be accessed via get.tfr3.convergence.

Value

has.mcmc.converged returns a logical value determining if there is convergence or not.

tfr.diagnose and tfr3.diagnose return an object of class bayesTFR.convergence with components:

result

Table containing all not-converged parameters. Its columns include ‘Total iterations needed’ and ‘Remaining iterations’.

lresult.country.independent

Number of rows in result that correspond to country-independent paramters. These rows are groupped at the beginning of the table.

country.independent

Result of tfr.raftery.diag processed on country-independent parameters.

country.specific

Result of tfr.raftery.diag processed on country-specific parameters.

iter.needed

Number of additional iterations suggested in order to achieve convergence.

iter.total

Total number of iterations of the original unthinned set of chains.

use.nr.traj

Suggestion for number of trajectories in generating predictions.

burnin

Burnin used.

thin

Thinning interval used.

status

Vector of character strings containing the result status. Possible values: ‘green’, ‘red’.

mcmc.set

Object of class bayesTFR.mcmc.set that corresponds to the original set of MCMCs on which the diagnostics was run.

thin.mcmc

If keep.thin.mcmc is TRUE, it is an object of class bayesTFR.mcmc.set that corresponds to the thinned mcmc set on which the diagnostics was run, otherwise NULL.

express

Value of the input argument express.

nr.countries

Vector with elements used - number of countries used in this diagnostics, and total - number of countries that this mcmc.set object was estimated on.

Author(s)

Hana Sevcikova, Leontine Alkema, Adrian Raftery

See Also

tfr.raftery.diag, raftery.diag, summary.bayesTFR.convergence, get.tfr.convergence, create.thinned.tfr.mcmc


[Package bayesTFR version 7.0-4 Index]