# BootCI: Simple Bootstrap Confidence Intervals In DescTools: Tools for Descriptive Statistics

## Description

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

## Usage

 ```1 2``` ```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:

 `` 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>

`MeanCI`, `MedianCI`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```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) ```

### Example output

```    mean   lwr.ci   upr.ci
47.93667 47.41901 48.51006
mean   lwr.ci   upr.ci
48.98024 48.38009 49.61622
Skew     lwr.ci     upr.ci
-0.8418683 -0.9410722 -0.7475509
CramerV     lwr.ci     upr.ci
0.08670047 0.04166906 0.11592812
spearman     lwr.ci     upr.ci
-0.5734425 -0.6206271 -0.5292857
```

DescTools documentation built on June 17, 2021, 5:12 p.m.