# svycdf: Cumulative Distribution Function In survey: Analysis of Complex Survey Samples

 svycdf 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`)

`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)
``````

survey documentation built on May 3, 2023, 9:12 a.m.