R: Simple Bootstrap Confidence Intervals

BootCI {DescTools} | R Documentation

## Simple Bootstrap Confidence Intervals

### Description

Convenience wrapper for calculating bootstrap confidence intervals for univariate and bivariate statistics.

### Usage

    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)

### Arguments

`x` | a (non-empty) numeric vector of data values.
`y` | NULL (default) or a vector with compatible dimensions to `x`, when a bivariate statistic is used.
`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 `"norm"`, `"basic"`, `"stud"`, `"perc"`, `"bca"`, as it is passed on as `method` to `boot.ci`.
`conf.level` | confidence level of the interval.
`sides` | a character string specifying the side of the confidence interval, must be one of `"two.sided"` (default), `"left"` or `"right"`. You can specify just the initial letter. `"left"` would be analogue to a hypothesis of `"greater"` in a `t.test`.
`...` | further arguments are passed to the function `FUN`.
`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 `R` would be a vector of integers where each component gives the number of resamples from each of the rows of weights.

### Value

a named numeric vector with 3 elements:

`<FUN>` | the specific estimate, as calculated by `FUN`
`lwr.ci` | lower bound of the confidence interval
`upr.ci` | upper bound of the confidence interval

### Author(s)

Andri Signorell <andri@signorell.net>

### See Also

`MeanCI`, `MedianCI`

### Examples

    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)

[Package DescTools version 0.99.38 Index]