tfr.estimation.plot: Plot TFR Estimation

In PPgp/bayesTFR: Bayesian Fertility Projection

Plot TFR Estimation

Description

Plot past TFR estimation results from a simulation that accounted for past TFR uncertainty.

Usage

tfr.estimation.plot(mcmc.list = NULL, country = NULL, sim.dir = NULL, 
    burnin = 0, thin = 1, pis = c(80, 95), plot.raw = TRUE, 
    grouping = "source", save.image = TRUE, plot.dir = "Estimation.plot", 
    adjust = TRUE, country.code = deprecated(), ISO.code = deprecated())

Arguments

mcmc.list	Object of class bayesTFR.mcmc.set corresponding Phase II MCMCs. If it is NULL, the object is loaded from the directory given by sim.dir.
country	Name or numerical code of a country. It can also be given as ISO-2 or ISO-3 characters.
sim.dir	Directory with the MCMC simulation results.
burnin	Burn-in for getting trajectories and quantiles. A positive burn-in x will remove first x iterations from each chain.
thin	Thin for getting trajectories and quantiles. Thinning level x greater than 1 will store one iteration per x samples
pis	Probability interval. It can be a single number or an array of two numbers.
plot.raw	Whether raw data used for the estimation should be plotted.
grouping	If raw data is plotted, then grouping should be one of the categorical feature in the data, so that the color and shape of the raw data will differ for different groups.
save.image	Logical. Whether the resulting plot will be saved.
plot.dir	If save.image=TRUE, specify the directory for saving the plot.
adjust	Logical. By default, if the estimation median is adjusted using e.g. tfr.median.set.all, the function plots the adjusted median. If adjust=FALSE the original (non-adjusted) median is plotted.
country.code, ISO.code	Deprecated arguments. Use argument country instead.

Details

tfr.estimation.plot plots posterior distribution of past TFR estimations for a given country. It only works if uncertainty is considered in the MCMC process.

Author(s)

Peiran Liu, Hana Sevcikova

Examples

## Not run: 
sim.dir <- tempfile()
mcmc.set <- run.tfr.mcmc(nr.chains = 1, iter = 10, output.dir = sim.dir, 
    replace.output = TRUE, uncertainty = TRUE)
tfr.estimation.plot(mcmc.set, "Nigeria", save.image = FALSE)
unlink(sim.dir, recursive = TRUE)
## End(Not run)

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