R: Cumulative Distribution Function

svycdf {survey} | R Documentation

## Cumulative Distribution Function

### Description

Estimates the population cumulative distribution function for specified variables. In contrast to `svyquantile`, this does not do any interpolation: the result is a right-continuous step function.

### Usage

    svycdf(formula, design, na.rm = TRUE,...)
    ## S3 method for class 'svycdf'
    print(x,...)
    ## S3 method for class 'svycdf'
    plot(x,xlab=NULL,...)

### Arguments

`formula` | one-sided formula giving variables from the design object
`design` | survey design object
`na.rm` | remove missing data (case-wise deletion)?
`...` | other arguments to `plot.stepfun`
`x` | object of class `svycdf`
`xlab` | a vector of x-axis labels or `NULL` for the default labels

### Value

An object of class `svycdf`, which is a list of step functions (of class `stepfun`)

### See Also

`svyquantile`, `svyhist`, `plot.stepfun`

### Examples

    data(api)
    dstrat <- svydesign(id = ~1, strata = ~stype, weights = ~pw, data = apistrat,
        fpc = ~fpc)
    cdf.est<-svycdf(~enroll+api00+api99, dstrat)
    cdf.est
    ## function
    cdf.est[[1]]
    ## evaluate the function
    cdf.est[[1]](800)
    cdf.est[[2]](800)

    ## compare to population and sample CDFs.
    opar<-par(mfrow=c(2,1))
    cdf.pop<-ecdf(apipop$enroll)
    cdf.samp<-ecdf(apistrat$enroll)
    plot(cdf.pop,main="Population vs sample", xlab="Enrollment")
    lines(cdf.samp,col.points="red")

    plot(cdf.pop, main="Population vs estimate", xlab="Enrollment")
    lines(cdf.est[[1]],col.points="red")

    par(opar)

[Package survey version 3.32-1 Index]