tidy.kde: Tidy a(n) kde object

Description

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 kde
tidy(x, ...)

Value

A tibble::tibble() with columns:

estimate: The estimated value of the regression term.
obs: weighted observed number of events in each group.
value: The value/estimate of the component. Results from data reshaping.
variable: Variable under consideration.

Arguments

x

A kde object returned from ks::kde().

...

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.

Details

Returns a data frame in long format with four columns. Use tidyr::pivot_wider(..., names_from = variable, values_from = value) on the output to return to a wide format.

Examples

Run this code

if (FALSE) { # rlang::is_installed(c("ks", "ggplot2"))

# load libraries for models and data
library(ks)

# generate data
dat <- replicate(2, rnorm(100))
k <- kde(dat)

# summarize model fit with tidiers + visualization
td <- tidy(k)
td

library(ggplot2)
library(dplyr)
library(tidyr)

td %>%
  pivot_wider(c(obs, estimate),
    names_from = variable,
    values_from = value
  ) %>%
  ggplot(aes(x1, x2, fill = estimate)) +
  geom_tile() +
  theme_void()

# also works with 3 dimensions
dat3 <- replicate(3, rnorm(100))
k3 <- kde(dat3)

td3 <- tidy(k3)
td3
}