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Create a plot of the posterior density distributions of modeled parameters from brmsfit model

posterior_densities_plot.Rd

plots the brmsfit model density distribution of each parameter and the mean, lower confidence interval, and upper confidence interval.

Usage

posterior_densities_plot(
  model,
  predictors_col_name = "_Intercept",
  half_max_label = "ec50",
  l_ci = 0.025,
  u_ci = 0.975,
  title_label = "Posterior Density Plots w/ Mean & 95% CI"
)

Arguments

model

brmsfit model.

predictors_col_name

string expression for predictors column in the input data.frame (default = "_Intercept"). Predictors are the perturbations tested during the experiment (i.e. Drug, Temperature, etc.).

half_max_label

string of the label for the half maximal that fits the type of experiment that was done (i.e. ec50, ic50, ed50, id50, ld50, etc.).

l_ci

numeric unit of the lower confidence interval (default = 0.025)

u_ci

numeric unit of the upper confidence interval (default = 0.975)

title_label

string of the plot title. (default = "Posterior Density Plots with Mean and 95% CI")

Value

ggplot2::ggplot object.

Examples

if (FALSE) {
  posterior_densities_plot(
    model = my_sigmoid_model,
    predictors_col_name = "predictors",
    half_max_label = "ic50",
    l_ci = 0.025,
    u_ci = 0.975,
    title_label = "Posterior Density Plots with Mean and 95% CI")
}