bayesTFR (version 7.4-2)

get.est.model: Accessing estimated bias and standard deviations

Description

Functions for obtaining bias and standard deviation of the estimated models as well as the model fits.

Usage

tfr.bias.sd(mcmc.list = NULL, country = NULL, sim.dir = NULL, ...)
get.bias.model(mcmc.list = NULL, country = NULL, sim.dir = NULL, ...)
get.std.model(mcmc.list = NULL, country = NULL, sim.dir = NULL, ...)

Value

Functions get.bias.model and get.std.model return a list with

model

lm object corresponding to the linear model used to estimate the bias (in case of get.bias.model) and standard deviation (in case of get.std.model).

table

data.frame object storing the bias/standard deviation of all possible combinations in the raw data sets for the given country.

Function tfr.bias.sd consolidates these items into a single list where the elements are model_bias, model_sd and table.

Arguments

mcmc.list

Object of class bayesTFR.mcmc.set corresponding to 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. Only used if mcmc.list is not given.

...

Not used.

Author

Peiran Liu, Hana Sevcikova

Details

Functions get.bias.model and get.std.model are used to obtain the model fit for estimated bias and standard deviation, respectively, when uncertainty about input data is taken into account. These are used in the MCMC steps stored in mcmc.list. Function tfr.bias.sd combines both infos into one object.

Examples

if (FALSE) {
sim.dir <- tempfile()
mcmc.set <- run.tfr.mcmc(nr.chains = 1, iter = 10, 
    output.dir = sim.dir, uncertainty = TRUE)
tfr.bias.sd(mcmc.set, "Nigeria")
unlink(sim.dir, recursive = TRUE)}