plot_ll: Plot Log-Likelihood vs. Values of One Parameter
In dvmisc: Convenience Functions, Moving Window Statistics, and Graphics

Description Usage Arguments Details Value Examples

Generates plot of log-likelihood vs. one parameter of interest while other parameters are held fixed at certain values (e.g. MLEs). This is not a profile likelihood, and is mainly intended for use with a Shiny app.

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plot_ll(start, objective, lower = -Inf, upper = Inf, xaxis_param = 1,
  xaxis_range = NULL, param_values = NULL, mles = NULL,
  return_info = FALSE)

`start`	See `nlminb`.
`objective`	See `nlminb`.
`lower`	See `nlminb`.
`upper`	See `nlminb`.
`xaxis_param`	Integer value specifying which parameter should be plotted on the x-axis.
`xaxis_range`	Numeric vector specifying x-axis range over which to vary the parameter of interest. Only values with likelihood ratio > 0.01 are ultimately plotted.
`param_values`	Numeric vector of values to use for other parameters in model, in case you want an additional curve for log-likelihood function vs. parameter of interest at certain non-MLE values for other parameters. For example, if there are 3 parameters and `xaxis_param = 2`, you could set `param_values = c(0, NA, 0)`.
`mles`	Numeric vector of previously obtained maximum likelihood estimates.
`return_info`	Logical value for whether to return the estimated MLEs and 99.99% confidence intervals for parameters rather than create the plot.

Note that objective should be the negative log-likelihood function, since internal optimization uses (nlminb), which does minimization.

Plot of log-likelihood vs. value of parameter of interest, generated by ggplot.

# Generate normal data, define log-likelihood function, and plot likelihood
set.seed(123)
x <- rnorm(100, mean = 0.5, sd = sqrt(0.25))
ll.f <- function(theta) {
  return(-sum(dnorm(x, log = TRUE, mean = theta[1], sd = sqrt(theta[2]))))
}
plot_ll(start = c(0, 1), objective = ll.f, lower = c(-Inf, 1e-6))