Tidy a(n) mle2 object

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

# S3 method for mle2
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

Arguments

x	An mle2 object created by a call to bbmle::mle2().
conf.int	Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to FALSE.
conf.level	The confidence level to use for the confidence interval if conf.int = TRUE. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.
...	Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

See also

tidy(), bbmle::mle2(), tidy_optim()

Examples

if (require("bbmle", quietly = TRUE)) {
  x <- 0:10
  y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8)
  d <- data.frame(x,y)

  fit <- mle2(y ~ dpois(lambda = ymean),
              start = list(ymean = mean(y)), data = d)

  tidy(fit)
}
#> Warning: there is no package called ‘bbmle’