plot_param {poolABC}

Plot the density estimation of a given parameter

Description

Plots the density estimation of a single parameter for quick visualization of the quality of an ABC analysis.

Usage

plot_param(prior, posterior, limits, index, weights = NULL)

Arguments

prior

is a vector or matrix of simulated parameter values i.e. numbers from the simulations. Each row or vector entry should be a different simulation and each column of a matrix should be a different parameter. This corresponds to the prior distribution and it should contain all the simulated parameter values.

posterior

is either a list or a matrix with samples from the posterior distributions obtained for each target. If in list format, each entry should be a matrix where each row corresponds to a different accepted simulations and each column corresponds to a different parameter.

limits

is a matrix with two columns and as many rows as there are parameters. Each row should contain the minimum value of the prior for a given parameter in the first column and the maximum value in the second column.

index

is an non-negative integer indicating which parameter to plot. It corresponds to the desired column of a matrix in the posteriors input. So, to plot the first parameter, corresponding to the first column in the posteriors input select 1. To plot the second parameter, select 2 and so on.

weights

is an optional list input containing the weights from the local linear regression method. Each entry of the list should be a numeric vector with the weights for each accepted simulation.

Details

This function can be used for a quick visualization of the posterior distribution obtained for a single target with the singleABC() function. Alternatively, if parameter estimation was performed with the multipleABC() function, the multiple posterior distributions, each obtained for a different target, will be combined into a single matrix and all values will be considered samples from the same posterior distribution.

Value

a plot of the density estimation of a given parameter. This plot will include a title with the name of the parameter. It will also include the density of the prior distribution for that parameter.

Examples

# load the matrix with parameter values
data(params)
# load the matrix with simulated parameter values
data(sumstats)
# load the matrix with the prior limits
data(limits)

# select a random simulation to act as target just to test the function
target <- sumstats[15 ,]
# we should remove the random simulation from the sumstats and params matrices
sumstats <- sumstats[-15, ]; params <- params[-15, ]

# parameter estimation for a single target
myabc <- singleABC(target = target, params = params, sumstats = sumstats, limits = limits,
tol = 0.01, method = "regression")

# plot the density estimation of a given parameter
plot_param(prior = params, posterior = myabc$adjusted, limits = limits,
index = 6, weights = myabc$weights)

# note that this is just an example!
# we don't have enough simulations to obtain credible results