Description Objects from the Class Slots Extends Methods Author(s) See Also Examples

Create a list of Euclidean random variables

Objects can be created by calls of the form `new("EuclRandVarList", ...)`

.
More frequently they are created via the generating function
`EuclRandVarList`

.

`.Data`

Object of class

`"list"`

. A list of Euclidean random variables.

Class `"list"`

, from data part.

Class `"vector"`

, by class `"list"`

.

- coerce
`signature(from = "EuclRandVariable", to = "EuclRandVarList")`

: create a`"EuclRandVarList"`

object from a Euclidean random variable.- coerce
`signature(from = "EuclRandMatrix", to = "EuclRandVarList")`

: create a`"EuclRandVarList"`

object from a Euclidean random matrix.- numberOfMaps
`signature(object = "EuclRandVarList")`

: number of functions contained in the slots`Map`

of the members of`object`

.- dimension
`signature(object = "EuclRandVarList")`

: dimension of the Euclidean random variable.- evalRandVar
`signature(RandVar = "EuclRandVarList", x = "numeric")`

: evaluate the elements of`RandVar`

at`x`

.- evalRandVar
`signature(RandVar = "EuclRandVarList", x = "matrix")`

: evaluate the elements of`RandVar`

at rows of`x`

.- evalRandVar
`signature(RandVar = "EuclRandVarList", x = "numeric", distr = "Distribution")`

: evaluate the elements of`RandVar`

at`x`

assuming a probability space with distribution`distr`

. In case`x`

does not lie in the support of`distr`

`NA`

is returned.- evalRandVar
`signature(RandVar = "EuclRandVarList", x = "matrix", distr = "Distribution")`

: evaluate the elements of`RandVar`

at rows of`x`

assuming a probability space with distribution`distr`

. For those rows of`x`

which do not lie in the support of`distr`

`NA`

is returned.- imageDistr
`signature(RandVar = "EuclRandVarList", distr = "Distribution")`

: image distribution of`distr`

under`RandVar`

. Returns an object of class`"DistrList"`

.- show
`signature(object = "EuclRandVarList")`

- t
`signature(x = "EuclRandVarList")`

: returns an object of class`"EuclRandVarList"`

where the rhe results of the functions in the slots`Map`

of the members of`x`

are transposed.- %m%
`signature(x = "EuclRandVarList", y = "EuclRandVarList")`

: matrix multiplication for objects of class`"EuclRandVarList"`

. Generates an object of class`"EuclRandVarList"`

.- %*%
`signature(x = "matrix", y = "EuclRandVarList")`

: matrix multiplication of`x`

and`y`

. Generates an object of class`"EuclRandMatrix"`

.- %*%
`signature(x = "EuclRandVarList", y = "matrix")`

: matrix multiplication of`x`

and`y`

. Generates an object of class`"EuclRandMatrix"`

.- Arith
`signature(e1 = "numeric", e2 = "EuclRandVarList")`

: Given a numeric vector`e1`

, a list of Euclidean random variables`e2`

and an arithmetic operator`op`

, the list of Euclidean random variables`e1 op e2`

is returned.- Arith
`signature(e1 = "EuclRandVarList", e2 = "numeric")`

: Given a numeric vector`e2`

, a list of Euclidean random variables`e1`

and an arithmetic operator`op`

, the list of Euclidean random variables`e1 op e2`

is returned.- Arith
`signature(e1 = "EuclRandVarList", e2 = "EuclRandVarList")`

: Given two lists of Euclidean random variables`e1`

,`e2`

and an arithmetic operator`op`

, the list of Euclidean random variables`e1 op e2`

is returned.- Math
`signature(x = "EuclRandVarList")`

: Given a`"Math"`

group generic`fct`

, the list of Euclidean random variables`fct(x)`

is returned.- E
`signature(object = "UnivariateDistribution", fun = "EuclRandVarList", cond = "missing")`

: expectation of`fun`

under univariate distributions.- E
`signature(object = "AbscontDistribution", fun = "EuclRandVarList", cond = "missing")`

: expectation of`fun`

under absolutely continuous univariate distributions.- E
`signature(object = "DiscreteDistribution", fun = "EuclRandVarList", cond = "missing")`

: expectation of`fun`

under discrete univariate distributions.- E
`signature(object = "MultivariateDistribution", fun = "EuclRandVarList", cond = "missing")`

: expectation of`fun`

under multivariate distributions.- E
`signature(object = "DiscreteMVDistribution", fun = "EuclRandVarList", cond = "missing")`

: expectation of`fun`

under discrete multivariate distributions.- E
`signature(object = "UnivariateCondDistribution", fun = "EuclRandVarList", cond = "numeric")`

: expectation of`fun`

under conditional univariate distributions.- E
`signature(object = "AbscontCondDistribution", fun = "EuclRandVarList", cond = "numeric")`

: expectation of`fun`

under absolutely continuous conditional univariate distributions.- E
`signature(object = "DiscreteCondDistribution", fun = "EuclRandVarList", cond = "numeric")`

: expectation of`fun`

under discrete conditional univariate distributions.

Matthias Kohl [email protected]

`EuclRandMatrix`

, `RandVariable-class`

,
`EuclRandVariable-class`

, `EuclRandMatrix-class`

,
`Distribution-class`

, `Arith`

,
`Math`

, `E`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
L1 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4},
function(x){x^5}, function(x){x^6})
L2 <- list(function(x){exp(x)}, function(x){abs(x)},
function(x){sin(x)}, function(x){floor(x)})
R1 <- new("EuclRandVariable", Map = L2, Domain = Reals(), Range = Reals())
R2 <- EuclRandMatrix(Map = L1, ncol = 2, Domain = Reals(), dimension = 1)
R3 <- EuclRandMatrix(Map = L2, ncol = 2, Domain = Reals(), dimension = 1)
(RL1 <- new("EuclRandVarList", list(R1, R2, R3)))
dimension(RL1)
as(R1, "EuclRandVarList")
as(R2, "EuclRandVarList")
Map(exp(RL1)[[1]]) # "Math" group
## "Arith" group
Map((1 + RL1)[[1]])
Map((RL1 * 2)[[2]])
Map((RL1 / RL1)[[3]])
``` |

RandVar documentation built on May 2, 2019, 5:20 p.m.

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