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 Kendall
tidy(x, ...)
A Kendall
object returned from a call to Kendall::Kendall()
,
Kendall::MannKendall()
, or Kendall::SeasonalMannKendall()
.
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.
A tibble::tibble()
with columns:
Kendall score.
The two-sided p-value associated with the observed statistic.
Variance of the kendall_score.
Kendall's tau statistic
The denominator, which is tau=kendall_score/denominator.
# feel free to ignore the following line—it allows {broom} to supply
# examples without requiring the model-supplying package to be installed.
if (requireNamespace("Kendall", quietly = TRUE)) {
# load libraries for models and data
library(Kendall)
A <- c(2.5, 2.5, 2.5, 2.5, 5, 6.5, 6.5, 10, 10, 10, 10, 10, 14, 14, 14, 16, 17)
B <- c(1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2)
# fit models and summarize results
f_res <- Kendall(A, B)
tidy(f_res)
s_res <- MannKendall(B)
tidy(s_res)
t_res <- SeasonalMannKendall(ts(A))
tidy(t_res)
}
#> # A tibble: 1 × 5
#> statistic p.value kendall_score denominator var_kendall_score
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 0.924 0.000000935 116 126. 559.