E

From distrEx v0.4-2 by Matthias Kohl

Generic Function for the Computation of (Conditional) Expectations

Generic function for the computation of (conditional) expectations.

Keywords: methods, distribution

Usage

E(object, fun, cond, ...)

## S3 method for class 'UnivariateDistribution,function,missing':
E(object, fun, cond, useApply = TRUE, ...)

## S3 method for class 'AbscontDistribution,function,missing':
E(object, fun, cond, useApply = TRUE, ...)

## S3 method for class 'DiscreteDistribution,function,missing':
E(object, fun, cond, useApply = TRUE, ...)

## S3 method for class 'MultivariateDistribution,function,missing':
E(object, fun, cond, useApply = TRUE, ...)

## S3 method for class 'DiscreteMVDistribution,function,missing':
E(object, fun, cond, useApply = TRUE, ...)

## S3 method for class 'AbscontCondDistribution,missing,numeric':
E(object, cond, useApply = TRUE)

## S3 method for class 'DiscreteCondDistribution,missing,numeric':
E(object, cond, useApply = TRUE)

## S3 method for class 'UnivariateCondDistribution,function,numeric':
E(object, fun, cond, withCond = FALSE, useApply = TRUE, ...)

## S3 method for class 'AbscontCondDistribution,function,numeric':
E(object, fun, cond, withCond = FALSE, useApply = TRUE, ...)

## S3 method for class 'DiscreteCondDistribution,function,numeric':
E(object, fun, cond, withCond = FALSE, useApply = TRUE, ...)

Arguments

object: object of class "Distribution"
fun: if missing the (conditional) expectation is computed else the (conditional) expection of fun is computed.
cond: if not missing the conditional expectation given cond is computed.
...: additional arguments to fun
useApply: logical: should sapply, respectively apply be used to evaluate fund.
withCond: logical: is cond in the argument list of fun.

Details

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

Value

The (conditional) expectation is computed.

concept

expectation
conditional expectation
integration

Examples

# mean of Exp(1) distribution
E(Exp())

# second moment of N(1,4)
E(Norm(mean=1, sd=2), fun = function(x){x^2})
E(Norm(mean=1, sd=2), fun = function(x){x^2}, useApply = FALSE)

# conditional distribution of a linear model
D1 <- LMCondDistribution(theta = 1) 
E(D1, cond = 1)
E(Norm(mean=1))
E(D1, function(x){x^2}, cond = 1)
E(Norm(mean=1), fun = function(x){x^2})
E(D1, function(x, cond){cond*x^2}, cond = 2, withCond = TRUE, useApply = FALSE)
E(Norm(mean=2), function(x){2*x^2})

Documentation reproduced from package distrEx, version 0.4-2, License: GPL (version 2 or later)

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E