e0.DLcurve.plot {bayesLife}

Plotting Posterior Distribution of the Double Logistic Function of Life Expectancy

Description

The functions plot the posterior distribution of the double logistic function used in the simulation, including their median and given probability intervals.

Usage

e0.DLcurve.plot(mcmc.list, country, burnin = NULL, pi = 80, 
    e0.lim = NULL, nr.curves = 20, predictive.distr = FALSE, ylim = NULL, 
    xlab = "e(0)", ylab = "5-year gains", main = NULL, show.legend = TRUE, 
    col = c('black', 'red', "#00000020"), ...)
    
e0.DLcurve.plot.all(mcmc.list = NULL, sim.dir = NULL, 
    output.dir = file.path(getwd(), "DLcurves"),
    output.type = "png", burnin = NULL, verbose = FALSE, ...)
    
e0.parDL.plot(mcmc.set, country = NULL, burnin = NULL, lty = 2, 
    ann = TRUE, ...)
	
e0.world.dlcurves(x, mcmc.list, burnin = NULL, ...)

e0.country.dlcurves(x, mcmc.list, country, burnin = NULL, ...)

Arguments

mcmc.list

List of bayesLife.mcmc objects, an object of class bayesLife.mcmc.set or of class bayesLife.prediction. In case of e0.DLcurve.plot.all if it si NULL, it is loaded from sim.dir.

mcmc.set

Object of class bayesLife.mcmc.set or bayesLife.prediction.

country

Name or numerical code of a country. It can also be given as 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.

e0.lim

It can be a tuple of the minimum and maximum life expectancy to be shown in the plot. If NULL, it takes the minimum of observed data and 40, and the maximum of observed data and 90.

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, lty

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

...

Additional graphical parameters. In addition, any arguments from e0.DLcurve.plot except country can be passed to e0.DLcurve.plot.all.

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

e0 values for which the double logistic should be computed.

ann

Logical if parameters should be annotated.

Details

e0.DLcurve.plot plots double logistic curves for the given country. e0.DLcurve.plot.all creates such plots for all countries and stores them in output.dir. Parameters passed to the double logistic function are either thinned traces created by the e0.predict function (if mcmc.list is an object of class bayesLife.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 e0.parDL.plot draws the means of the DL parameters as vertical and horizontal lines. The lines are added to the current graphical device and annotated if ann is TRUE. If country is NULL, the mean of world parameters are drawn.

Function e0.world.dlcurves returns the DL curves of the hierarchical distribution. Function e0.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

e0.world.dlcurves and e0.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.

Author(s)

Hana Sevcikova

Examples

## Not run: 
sim.dir <- file.path(find.package("bayesLife"), "ex-data", "bayesLife.output")
mcmc.set <- get.e0.mcmc(sim.dir = sim.dir)
e0.DLcurve.plot(mcmc.set, country = "Japan", burnin = 40)
e0.parDL.plot(mcmc.set, "Japan")

# add the median of the hierarchical DL curves
x <- seq(40, 90, length = 100)
world <- e0.world.dlcurves(x, mcmc.set, burnin = 40)
qw <- apply(world, 2, median) 
lines(x, qw, col = 'blue')

## End(Not run)