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 across 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 fitdistr tidy(x, ...)
x | A |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Other fitdistr tidiers:
glance.fitdistr()
A tibble::tibble()
with columns:
The estimated value of the regression term.
The standard error of the regression term.
The name of the regression term.
if (requireNamespace("MASS", quietly = TRUE)) { set.seed(2015) x <- rnorm(100, 5, 2) library(MASS) fit <- fitdistr(x, dnorm, list(mean = 3, sd = 1)) tidy(fit) glance(fit) } #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> Warning: NaNs produced #> # A tibble: 1 × 4 #> logLik AIC BIC nobs #> <logLik> <dbl> <dbl> <int> #> 1 -211.6533 427. 433. 100