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, ...)
x | A |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble with one row for estimated parameter, with columns:
The term that was estimated
Estimated value
Standard error of estimate
Other fitdistr tidiers: glance.fitdistr
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 producedtidy(fit)#> # A tibble: 2 x 3 #> term estimate std.error #> <chr> <dbl> <dbl> #> 1 mean 4.90 0.201 #> 2 sd 2.01 0.142glance(fit)#> # A tibble: 1 x 4 #> n logLik AIC BIC #> <int> <dbl> <dbl> <dbl> #> 1 100 -212. 427. 433.