Check apc object, whether MCMC has converged

This function uses Gelman and Rubin's R (potential scale reduction factor) to check convergence. All checked quantities should have R<1.1. bamp runs at least four MCMC chains by default (more if parallel is more than four).

Usage

checkConvergence(x, info = FALSE, level = 2, auto = FALSE)

Arguments

x: An apc object
info: logical; print more information (including the raw per-effect diagnostic, which is affected by the age-period-cohort identifiability and should not be used on its own, see Details)
level: level of check; 1 uses point estimate, 2 uses upper C.I.
auto: logical; should be TRUE if called automatically from bamp

Value

logical; TRUE if check is fine.

Details

In an age-period-cohort model the age, period and cohort effects are linearly dependent (Clayton and Schifflers, 1987): a linear trend can be moved between the three effects without changing the likelihood. The individual effect chains can therefore drift along this non-identified direction even when the model has fully converged, which makes a naive Gelman-R on the raw effects report spurious non-convergence.

checkConvergence therefore assesses the quantities that are actually identified: the smoothing precisions, the intercept, and the fitted linear predictor (log-odds) in every cell of the Lexis diagram, which is invariant to the trend re-allocation. With info=TRUE the raw per-effect diagnostic is also printed for reference.

Examples

if (FALSE) { # \dontrun{
data(apc)
model <- bamp(cases, population, age="rw1", period="rw1", cohort="rw1", periods_per_agegroup = 5)
checkConvergence(model)
} # }