R: Working with a kde1d object

dkde1d {kde1d} | R Documentation

## Working with a kde1d object

### Description

Density, distribution function, quantile function and random generation for a 'kde1d' kernel density estimate.

### Usage

    dkde1d(x, obj)

    pkde1d(q, obj)

    qkde1d(p, obj)

    rkde1d(n, obj, quasi = FALSE)

### Arguments

`x` | vector of density evaluation points.
`obj` | a `kde1d` object.
`q` | vector of quantiles.
`p` | vector of probabilities.
`n` | integer; number of observations.
`quasi` | logical; the default (`FALSE`) returns pseudo-random numbers, use `TRUE` for quasi-random numbers (generalized Halton, see `randtoolbox::sobol()`).

### Details

`dkde1d()` gives the density, `pkde1d()` gives the distribution function, `qkde1d()` gives the quantile function, and `rkde1d()` generates random deviates.

The length of the result is determined by `n` for `rkde1d()`, and is the length of the numerical argument for the other functions.

### Value

The density, distribution function or quantile functions estimates evaluated respectively at `x`, `q`, or `p`, or a sample of `n` random deviates from the estimated kernel density.

### See Also

`kde1d()`

### Examples

    set.seed(0) # for reproducibility
    x <- rnorm(100) # simulate some data
    fit <- kde1d(x) # estimate density
    dkde1d(0, fit) # evaluate density estimate (close to dnorm(0))
    pkde1d(0, fit) # evaluate corresponding cdf (close to pnorm(0))
    qkde1d(0.5, fit) # quantile function (close to qnorm(0))
    hist(rkde1d(100, fit)) # simulate

[Package kde1d version 1.0.4 Index]