plot-DLcurve: Plotting Posterior Distribution of the Double Logistic...

In bayesTFR: Bayesian Fertility Projection

Plotting Posterior Distribution of the Double Logistic Function

Description

The functions for plotting and retrieving the posterior distribution of the double logistic function used in the simulation of Phase II. Plots include the median and given probability intervals of the distribution.

Usage

DLcurve.plot(mcmc.list, country, burnin = NULL, pi = 80, tfr.max = 10, 
    nr.curves = NULL, predictive.distr = FALSE, ylim = NULL, 
    xlab = 'TFR (reversed)', ylab = 'TFR decrement', main = NULL, 
    show.legend = TRUE, col=c('black', 'red', "#00000020"), ...)
	
DLcurve.plot.all(mcmc.list = NULL, sim.dir = NULL, 
    output.dir = file.path(getwd(), 'DLcurves'),
    output.type = "png", burnin = NULL, verbose = FALSE, ...)
    
tfr.world.dlcurves(x, mcmc.list, burnin=NULL, countryUc=NULL, ...)

tfr.country.dlcurves(x, mcmc.list, country, burnin=NULL, ...)

Arguments

mcmc.list	List of bayesTFR.mcmc objects, an object of class bayesTFR.mcmc.set or of class bayesTFR.prediction. In case of DLcurve.plot.all if it si NULL, it is loaded from sim.dir.
country	Name or code of a country. The code can be either numeric or ISO-2 or ISO-3 characters.
burnin	Number of iterations to be discarded from the beginning of parameter traces.
pi	Probability interval. It can be a single number or an array.
tfr.max	Maximum TFR to be shown in the plot.
nr.curves	Number of curves to be plotted. If NULL, all curves are plotted.
predictive.distr	Logical. If TRUE, an error term is added to each trajectory.
ylim, xlab, ylab, main	Graphical parameters passed to the plot function.
show.legend	Logical determining if the legend should be shown.
col	Vector of colors in this order: 1. observed data points, 2. quantiles, 3. trajectories
...	For the plotting functions, there are additional graphical parameters. For DLcurve.plot.all, ... contains also arguments pi, tfr.max and nr.curves. For the tfr.*.dlcurves functions, these are arguments passed to the underlying functions (predictive.distr and return.sigma for obtaining a sample of the standard deviation of the error term ).
sim.dir	Directory with the simulation results. Only relevant, if mcmc.list is NULL.
output.dir	Directory into which resulting graphs are stored.
output.type	Type of the resulting files. It can be “png”, “pdf”, “jpeg”, “bmp”, “tiff”, or “postscript”.
verbose	Logical switching log messages on and off.
x	TFR values for which the double logistic should be computed.
countryUc	Country to use the parameter U_c from (start of the fertility transition). If it is not given, the middle point of the prior distribution is used.

Details

DLcurve.plot plots double logistic curves for the given country. DLcurve.plot.all creates such plots for all countries and stores them in output.dir. Parameters inputting the double logistic function are either thinned traces created by the tfr.predict function (if mcmc.list is an object of class bayesTFR.prediction), or they are selected by equal spacing from the MCMC traces. In the former case, burnin is set automatically; in the latter case, burnin defaults to 0 since such object has already been “burned”. If nr.curves is smaller than 2000, the median and probability intervals are computed on a sample of 2000 equally spaced data points, otherwise on all plotted curves.

Function tfr.world.dlcurves returns the DL curves of the hierarchical distribution, conditioned on the starting point of the fertility transition in a given country (given by the countryUc argument). Function tfr.country.dlcurves returns DL curves for a given country. If mcmc.list is a prediction object, burnin should not be given, as such object has already been “burned”.

Value

tfr.world.dlcurves and tfr.country.dlcurves return a matrix of size N \times M where N is the number of trajectories and M is the number of values of x. If the argument return.sigma is set to TRUE, the return value is a list with the first element being the DL values and the second element being a matrix of the standard deviation of the DL error term sigma_eps.

Author(s)

Hana Sevcikova, Leontine Alkema

Examples

## Not run: 
sim.dir <- file.path(find.package("bayesTFR"), "ex-data", "bayesTFR.output")
mcmc.set <- get.tfr.mcmc(sim.dir=sim.dir)
DLcurve.plot(country="Burkina Faso", mcmc.set, burnin=15)

# add the median of the hierarchical DL curves
x <- seq(0, 10, length=100)
world <- tfr.world.dlcurves(x, mcmc.set, burnin=15, countryUc="Burkina Faso")
qw <- apply(world, 2, median) 
lines(x, qw, col='blue')

## End(Not run)

bayesTFR documentation built on April 4, 2025, 2:59 a.m.