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, ...)
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to
The confidence level to use for the confidence interval
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
tibble::tibble() with columns:
The upper end of a confidence interval for the term under consideration. Included only if `conf.int = TRUE`.
The lower end of a confidence interval for the term under consideration. Included only if `conf.int = TRUE`.
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The standard error of the regression term.
The name of the regression term.
library(bbmle)#>#> #>#>#> #>#>#> #>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)#> # A tibble: 1 x 5 #> term estimate std.error statistic p.value #> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 ymean 11.5 1.02 11.3 1.86e-29