EuclRandMatrix-class {RandVar} | R Documentation |
Euclidean random matrix
Description
Class of Euclidean random matrices.
Objects from the Class
Objects can be created by calls of the form new("EuclRandMatrix", ...)
.
More frequently they are created via the generating function
EuclRandMatrix
.
Slots
Dim
vector of positive integers: Dimensions of the random matrix.
Map
Object of class
"list"
: list of functions.Domain
Object of class
"OptionalrSpace"
domain of the random matrix.Range
Object of class
"OptionalrSpace"
range of the random matrix.
Extends
Class "EuclRandVariable"
, directly.
Class "RandVariable"
, by class "EuclRandVariable"
.
Methods
- coerce
signature(from = "EuclRandMatrix", to = "EuclRandVarList")
: create a"EuclRandVarList"
object from a Euclidean random matrix.- [
signature(x = "EuclRandMatrix")
: generates a new Euclidean random variable/matrix by extracting elements of the slotMap
ofx
.- Dim
signature(object = "EuclRandMatrix")
: accessor function for slotDim
.- Dim<-
signature(object = "EuclRandMatrix", )
: replacement function for slotDim
.- ncol
signature(x = "EuclRandMatrix")
: number of columns ofx
.- nrow
signature(x = "EuclRandMatrix")
: number of rows ofx
.- dimension
signature(object = "EuclRandMatrix")
: dimension of the Euclidean random variable.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "numeric")
: evaluate the slotMap
ofRandVar
atx
.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "matrix")
: evaluate the slotMap
ofRandVar
atx
.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "numeric", distr = "Distribution")
: evaluate the slotMap
ofRandVar
atx
assuming a probability space with distributiondistr
. In casex
does not lie in the support ofdistr
NA
is returned.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "matrix", distr = "Distribution")
: evaluate the slotMap
ofRandVar
at rows ofx
assuming a probability space with distributiondistr
. For those rows ofx
which do not lie in the support ofdistr
NA
is returned.- t
signature(x = "EuclRandMatrix")
: transposesx
. In addition, the results of the functions in the slotMap
ofx
are transposed.- show
signature(object = "EuclRandMatrix")
- %*%
signature(x = "matrix", y = "EuclRandMatrix")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- %*%
signature(x = "numeric", y = "EuclRandMatrix")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- %*%
signature(x = "EuclRandVariable", y = "EuclRandMatrix")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- %*%
signature(x = "EuclRandMatrix", y = "matrix")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- %*%
signature(x = "EuclRandMatrix", y = "numeric")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- %*%
signature(x = "EuclRandMatrix", y = "EuclRandMatrix")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- %*%
signature(x = "EuclRandMatrix", y = "EuclRandVariable")
: matrix multiplication ofx
andy
. Generates an object of class"EuclRandMatrix"
.- Arith
signature(e1 = "numeric", e2 = "EuclRandMatrix")
: Given a numeric vectore1
, a Euclidean random matrixe2
and an arithmetic operatorop
, the Euclidean random matrixe1 op e2
is returned.- Arith
signature(e1 = "EuclRandMatrix", e2 = "numeric")
: Given a Euclidean random matrixe1
, a numeric vectore2
, and an arithmetic operatorop
, the Euclidean random matrixe1 op e2
is returned.- Arith
signature(e1 = "EuclRandMatrix", e2 = "EuclRandMatrix")
: Given two Euclidean random matricese1
ande2
, and an arithmetic operatorop
, the Euclidean random matrixe1 op e2
is returned.- Math
signature(x = "EuclRandMatrix")
: Given a"Math"
group genericfct
, the Euclidean random matrixfct(x)
is returned.- E
signature(object = "UnivariateDistribution", fun = "EuclRandMatrix", cond = "missing")
: expectation offun
under univariate distributions.- E
signature(object = "AbscontDistribution", fun = "EuclRandMatrix", cond = "missing")
: expectation offun
under absolutely continuous univariate distributions.- E
signature(object = "DiscreteDistribution", fun = "EuclRandMatrix", cond = "missing")
: expectation offun
under discrete univariate distributions.- E
signature(object = "MultivariateDistribution", fun = "EuclRandMatrix", cond = "missing")
: expectation offun
under multivariate distributions.- E
signature(object = "DiscreteMVDistribution", fun = "EuclRandMatrix", cond = "missing")
: expectation offun
under discrete multivariate distributions.- E
signature(object = "UnivariateCondDistribution", fun = "EuclRandMatrix", cond = "numeric")
: conditional expectation offun
under conditional univariate distributions.- E
signature(object = "AbscontCondDistribution", fun = "EuclRandMatrix", cond = "numeric")
: conditional expectation offun
under absolutely continuous conditional univariate distributions.- E
signature(object = "DiscreteCondDistribution", fun = "EuclRandMatrix", cond = "numeric")
: conditional expectation offun
under discrete conditional univariate distributions.
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de
See Also
EuclRandMatrix
, RandVariable-class
,
EuclRandVariable-class
, EuclRandVarList-class
,
Distribution-class
, Arith
,
Math
, E
Examples
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("EuclRandMatrix", Map = L1, Dim = as.integer(c(3,2)),
Domain = Reals(), Range = Reals())
dimension(R1)
R1[1:2, 2]
R1[1:2, 1:2]
Map(R1[1,2])
Map(t(R1)[2,1])
R2 <- EuclRandMatrix(Map = L2, ncol = 2, Domain = Reals(), dimension = 1)
dimension(R2)
(DL <- imageDistr(R2, Norm()))
plot(DL)
Map(gamma(R2)) # "Math" group
## "Arith" group
Map(2/R1)
Map(R2 * R2)