Simple Bootstrap Confidence Intervals
Convenience wrapper for calculating bootstrap confidence intervals for univariate and bivariate statistics.
BootCI(x, y = NULL, FUN, ..., bci.method = c("norm", "basic", "stud", "perc", "bca"),
conf.level = 0.95, sides = c("two.sided", "left", "right"), R = 999)x |
a (non-empty) numeric vector of data values. |
y |
NULL (default) or a vector with compatible dimensions to |
FUN |
the function to be used |
bci.method |
A vector of character strings representing the type of intervals required. The value should be any subset of the values |
conf.level |
confidence level of the interval. |
sides |
a character string specifying the side of the confidence interval, must be one of |
... |
further arguments are passed to the function |
R |
The number of bootstrap replicates. Usually this will be a single positive integer. For importance resampling,
some resamples may use one set of weights and others use a different set of weights. In this case |
a named numeric vector with 3 elements:
<FUN> |
the specific estimate, as calculated by |
lwr.ci |
lower bound of the confidence interval |
upr.ci |
upper bound of the confidence interval |
Andri Signorell <andri@signorell.net>
set.seed(1984) BootCI(d.pizza$temperature, FUN=mean, na.rm=TRUE, bci.method="basic") BootCI(d.pizza$temperature, FUN=mean, trim=0.1, na.rm=TRUE, bci.method="basic") BootCI(d.pizza$temperature, FUN=Skew, na.rm=TRUE, bci.method="basic") BootCI(d.pizza$operator, d.pizza$area, FUN=CramerV) spearman <- function(x,y) cor(x, y, method="spearman", use="p") BootCI(d.pizza$temperature, d.pizza$delivery_min, FUN=spearman)
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