topolow (version 1.0.0)

plot.profile_likelihood: Plot Method for Profile Likelihood Objects

Description

Creates a visualization of profile likelihood for a parameter showing maximum likelihood estimates and confidence intervals. Supports mathematical notation for parameter names and configurable output settings.

Confidence interval is found using the likelihood ratio test: \(LR(\theta_{ij}) = -2[log L_{max}(\theta_{ij}) - log L_{max}(\hat{\theta})]\) where \(\hat{\theta}\) is the maximum likelihood estimate for all parameters. The 95% confidence interval is: \(\{\theta_{ij} : LR(\theta_{ij}) \leq \chi^2_{1,0.05} = 3.84\}\)

Usage

# S3 method for profile_likelihood
plot(x, LL_max, width = 3.5, height = 3.5, save_plot = FALSE, output_dir, ...)

Value

A ggplot object

Arguments

x

A profile_likelihood object

LL_max

Numeric maximum log-likelihood value

width

Numeric width of output plot in inches (default: 3.5)

height

Numeric height of output plot in inches (default: 3.5)

save_plot

Logical. Whether to save plot to file. Default: FALSE

output_dir

Character. Directory for output files. Required if save_plot is TRUE.

...

Additional arguments passed to plot

Examples

# These examples take more than 5 seconds to run, so they are not run by default. 
# Use parallel processing (the default) to speed up.
# \donttest{
# Create a sample data frame of MCMC samples
samples <- data.frame(
  log_N = log(runif(50, 2, 10)),
  log_k0 = log(runif(50, 1, 5)),
  log_cooling_rate = log(runif(50, 0.01, 0.1)),
  log_c_repulsion = log(runif(50, 0.1, 1)),
  NLL = runif(50, 20, 100)
)

# Calculate profile likelihood
pl_result <- profile_likelihood("log_N", samples, grid_size = 10)

# Plot with maximum likelihood from samples
LL_max <- max(-samples$NLL)
# The plot function requires the ggplot2 package
if (requireNamespace("ggplot2", quietly = TRUE)) {
  plot(pl_result, LL_max, width = 4, height = 3)
}
# }