Tidy a(n) boot object
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 'boot'
tidy(
x,
conf.int = FALSE,
conf.level = 0.95,
conf.method = c("perc", "bca", "basic", "norm"),
...
)x |
A |
conf.int |
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level |
The confidence level to use for the confidence interval
if |
conf.method |
Passed to the |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
If weights were provided to the boot function, an estimate
column is included showing the weighted bootstrap estimate, and the
standard error is of that estimate.
If there are no original statistics in the "boot" object, such as with a
call to tsboot with orig.t = FALSE, the original
and statistic columns are omitted, and only estimate and
std.error columns shown.
A tibble::tibble() with columns:
bias |
Bias of the statistic. |
std.error |
The standard error of the regression term. |
term |
The name of the regression term. |
statistic |
Original value of the statistic. |
if (requireNamespace("boot", quietly = TRUE)) {
library(boot)
clotting <- data.frame(
u = c(5, 10, 15, 20, 30, 40, 60, 80, 100),
lot1 = c(118, 58, 42, 35, 27, 25, 21, 19, 18),
lot2 = c(69, 35, 26, 21, 18, 16, 13, 12, 12)
)
g1 <- glm(lot2 ~ log(u), data = clotting, family = Gamma)
bootfun <- function(d, i) {
coef(update(g1, data = d[i, ]))
}
bootres <- boot(clotting, bootfun, R = 999)
tidy(g1, conf.int = TRUE)
tidy(bootres, conf.int = TRUE)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.