R: Histograms and boxplots

svyhist {survey} | R Documentation

## Histograms and boxplots

### Description

Histograms and boxplots weighted by the sampling weights.

### Usage

    svyhist(formula, design, breaks = "Sturges",
          include.lowest = TRUE, right = TRUE, xlab = NULL,
           main = NULL, probability = TRUE, freq = !probability, ...)
    svyboxplot(formula, design, all.outliers=FALSE,...)

### Arguments

`formula` | One-sided formula for `svyhist`, two-sided for `svyboxplot`
`design` | A survey design object
`xlab` | x-axis label
`main` | Main title
`probability,freq` | Y-axis is probability density or frequency
`all.outliers` | Show all outliers in the boxplot, not just extremes
`breaks, include.lowest, right` | As for `hist`
`...` | Other arguments to `hist` or `bxp`

### Details

The histogram breakpoints are computed as if the sample were a simple random sample of the same size.

The grouping variable in `svyboxplot`, if present, must be a factor.

The boxplot whiskers go to the maximum and minimum observations or to 1.5 interquartile ranges beyond the end of the box, whichever is closer. The maximum and minimum are plotted as outliers if they are beyond the ends of the whiskers, but other outlying points are not plotted unless `all.outliers=TRUE`. `svyboxplot` requires a two-sided formula; use `variable~1` for a single boxplot.

### See Also

`svyplot`

### Examples

    data(api)
    dstrat <- svydesign(id = ~1, strata = ~stype, weights = ~pw, data = apistrat,
        fpc = ~fpc)
    opar<-par(mfrow=c(1,3))
    svyhist(~enroll, dstrat, main="Survey weighted",col="purple",ylim=c(0,1.3e-3))
    hist(apistrat$enroll,  main="Sample unweighted",col="purple",prob=TRUE,ylim=c(0,1.3e-3))
    hist(apipop$enroll,  main="Population",col="purple",prob=TRUE,ylim=c(0,1.3e-3))

    par(mfrow=c(1,1))
    svyboxplot(enroll~stype,dstrat,all.outliers=TRUE)
    svyboxplot(enroll~1,dstrat)
    par(opar)

[Package survey version 3.32-1 Index]