tfr.diagnose: Convergence Diagnostics of TFR Markov Chain Monte Carlo

In PPgp/bayesTFR: Bayesian Fertility Projection

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

PPgp/bayesTFR documentation built on Nov. 5, 2024, 1:57 p.m.