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 fitdistr
tidy(x, ...)

Arguments

x

A fitdistr object returned by MASS::fitdistr().

...

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(), MASS::fitdistr()

Other fitdistr tidiers: glance.fitdistr

Value

A tibble::tibble() with columns:

estimate

The estimated value of the regression term.

std.error

The standard error of the regression term.

term

The name of the regression term.

Examples

set.seed(2015) x <- rnorm(100, 5, 2) library(MASS) fit <- fitdistr(x, dnorm, list(mean = 3, sd = 1))
#> 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
tidy(fit)
#> # A tibble: 2 x 3 #> term estimate std.error #> <chr> <dbl> <dbl> #> 1 mean 4.90 0.201 #> 2 sd 2.01 0.142
glance(fit)
#> # A tibble: 1 x 4 #> n logLik AIC BIC #> <int> <dbl> <dbl> <dbl> #> 1 100 -212. 427. 433.