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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.

Usage

# S3 method for class 'binWidth'
tidy(x, ...)

Arguments

x

A binGroup::binWidth() object.

...

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. Two exceptions here are:

  • tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

  • augment() methods will warn when supplied a newdata argument if it will be ignored.

See also

Value

A tibble::tibble() with columns:

alternative

Alternative hypothesis (character).

ci.width

Expected width of confidence interval.

p

True proportion.

n

Total sample size

Examples


# load libraries
library(binGroup)

# fit model
bw <- binWidth(100, .1)

bw
#> $expCIWidth
#> [1] 0.1256172
#> 
#> $alternative
#> [1] "two.sided"
#> 
#> $p
#> [1] 0.1
#> 
#> $n
#> [1] 100
#> 
#> attr(,"class")
#> [1] "binWidth"

# summarize model fit with tidiers
tidy(bw)
#> # A tibble: 1 × 4
#>   ci.width alternative     p     n
#>      <dbl> <chr>       <dbl> <dbl>
#> 1    0.126 two.sided     0.1   100