tidy.kde | R Documentation |
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 class 'kde' tidy(x, ...)
x |
A |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in
|
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.
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. |
tidy()
, ks::kde()
# 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
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