R: Generic Function for the Computation of Clipped First Moments

m1df {distrEx} | R Documentation

## Generic Function for the Computation of Clipped First Moments

### Description

Generic function for the computation of clipped first moments. The moments are clipped at `upper`.

### Usage

    m1df(object, upper, ...)
    ## S4 method for signature 'AbscontDistribution'
    m1df(object, upper,
                 lowerTruncQuantile = getdistrExOption("m1dfLowerTruncQuantile"),
                 rel.tol = getdistrExOption("m1dfRelativeTolerance"), ...)

### Arguments

`object` | object of class `"Distribution"`
`upper` | clipping bound
`rel.tol` | relative tolerance for `distrExIntegrate`.
`lowerTruncQuantile` | lower quantile for quantile based integration range.
`...` | additional arguments to `E`

### Details

The precision of the computations can be controlled via certain global options; cf. `distrExOptions`.

### Value

The first moment of `object` clipped at `upper` is computed.

### Methods

object = "UnivariateDistribution":

  uses call `E(object, upp=upper, ...)`.

object = "AbscontDistribution":

  clipped first moment for absolutely continuous univariate distributions which is computed using `integrate`.

object = "LatticeDistribution":

  clipped first moment for discrete univariate distributions which is computed using `support` and `sum`.

object = "AffLinDistribution":

  clipped first moment for affine linear distributions which is computed on basis of slot `X0`.

object = "Binom":

  clipped first moment for Binomial distributions which is computed using `pbinom`.

object = "Pois":

  clipped first moment for Poisson distributions which is computed using `ppois`.

object = "Norm":

  clipped first moment for normal distributions which is computed using `dnorm` and `pnorm`.

object = "Exp":

  clipped first moment for exponential distributions which is computed using `pexp`.

object = "Chisq":

  clipped first moment for Chi^2 distributions which is computed using `pchisq`.

### Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

### See Also

`distrExIntegrate`, `m2df`, `E`

### Examples

    # standard normal distribution
    N1 <- Norm()
    m1df(N1, 0)

    # Poisson distribution
    P1 <- Pois(lambda=2)
    m1df(P1, 3)
    m1df(P1, 3, fun = function(x)sin(x))

    # absolutely continuous distribution
    D1 <- Norm() + Exp() # convolution
    m1df(D1, 2)
    m1df(D1, Inf)
    E(D1)

[Package distrEx version 2.8.0 Index]