# qboxplot.stats: Helper Function For 'qboxplot' In qboxplot: Quantile-Based Boxplot

## Description

Produce quantile-based box-and-whisker plot(s) of the given (grouped) values.

## Usage

 `1` ```qboxplot.stats(x, probs, qtype, range, output="all") ```

## Arguments

 `x` a numeric vector of data values from which to calculate the requested statistics. `probs` numeric vector of values in [0,1] specifying the percentiles of the upper hinge, the midpoint (usually the median) and the lower hinge. `qtype` an integer between 1 and 9 indicating which one of the nine quantile algorithms to use (see `quantile`). `output` limit the output to `"quantiles"`, `"outliers"` or `"n"` (see below), or, if set to `"all"` (the default), outputs a list containing all three. `range` this determines how far the plot whiskers extend out from the box. If `range` is positive, the whiskers extend to the most extreme data point which is no more than `range` times the difference in the value of the upper hinge and the value of the lower hinge from the box. A value of zero causes the whiskers to extend to the data extremes.

## Value

List with the following components:

 `quantiles` a matrix, each column contains the extreme of the lower whisker, the lower hinge, the median, the upper hinge and the extreme of the upper whisker for one group/plot. `outliers` a vector with the number of observations in each group. `n` the values of any data points which lie beyond the extremes of the whiskers.

## Examples

 ```1 2 3``` ```x = runif(100) stats = qboxplot.stats(x, probs=c(0.4,0.5,0.6), qtype=7, range=1.5) stats ```

### Example output

```\$quantiles
 0.04008562 0.37046287 0.50688141 0.59756746 0.92386866

\$outliers
 0.94612795 0.01577551 0.95200619 0.94973380

\$n
 100
```

qboxplot documentation built on May 2, 2019, 8:35 a.m.