hist.mapbayests {mapbayr}

Plot posterior distribution of bayesian estimates

Description

Plot posterior distribution of bayesian estimates

Usage

## S3 method for class 'mapbayests'
hist(x, select_eta = x$arg.optim$select_eta, shk = c("sd", "var", NA), ...)

Arguments

x

A mapbayests object.

select_eta

a vector of numeric values, the numbers of the ETAs to show (default are estimated ETAs).

shk

method to compute the shrinkage if multiple subjects are analyzed. Possible values are "sd" (based on the ratio of standard deviation like in 'NONMEM'), "var" (based on the ratio of variances like 'Monolix'), or NA (do not show the shrinkage)

...

additional arguments (not used)

Details

Use this function to plot the results of the estimations, in the form of histograms with the a priori distribution in the background. For every parameter, the inter-individual variability is displayed, as well as the percentile of the patient in the corresponding distribution (if n = 1 patient). For additional modifications, you can add extra ⁠+function(...)⁠ in order to modify the plot as a regular ggplot2 object.

Value

a ggplot object.

Examples

est <- mapbayest(exmodel(ID = 1))

# Default Method
h <- hist(est)

# Can be modified with `ggplot2`
h +
  ggplot2::labs(title = "Awesome estimations")

# Select the ETAs
hist(est, select_eta = c(1,3))