| 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
Dimvector of positive integers: Dimensions of the random matrix.
MapObject of class
"list": list of functions.DomainObject of class
"OptionalrSpace"domain of the random matrix.RangeObject 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 slotMapofx.- 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 slotMapofRandVaratx.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "matrix"): evaluate the slotMapofRandVaratx.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "numeric", distr = "Distribution"): evaluate the slotMapofRandVaratxassuming a probability space with distributiondistr. In casexdoes not lie in the support ofdistrNAis returned.- evalRandVar
signature(RandVar = "EuclRandMatrix", x = "matrix", distr = "Distribution"): evaluate the slotMapofRandVarat rows ofxassuming a probability space with distributiondistr. For those rows ofxwhich do not lie in the support ofdistrNAis returned.- t
signature(x = "EuclRandMatrix"): transposesx. In addition, the results of the functions in the slotMapofxare transposed.- show
signature(object = "EuclRandMatrix")- %*%
signature(x = "matrix", y = "EuclRandMatrix"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- %*%
signature(x = "numeric", y = "EuclRandMatrix"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- %*%
signature(x = "EuclRandVariable", y = "EuclRandMatrix"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- %*%
signature(x = "EuclRandMatrix", y = "matrix"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- %*%
signature(x = "EuclRandMatrix", y = "numeric"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- %*%
signature(x = "EuclRandMatrix", y = "EuclRandMatrix"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- %*%
signature(x = "EuclRandMatrix", y = "EuclRandVariable"): matrix multiplication ofxandy. Generates an object of class"EuclRandMatrix".- Arith
signature(e1 = "numeric", e2 = "EuclRandMatrix"): Given a numeric vectore1, a Euclidean random matrixe2and an arithmetic operatorop, the Euclidean random matrixe1 op e2is returned.- Arith
signature(e1 = "EuclRandMatrix", e2 = "numeric"): Given a Euclidean random matrixe1, a numeric vectore2, and an arithmetic operatorop, the Euclidean random matrixe1 op e2is returned.- Arith
signature(e1 = "EuclRandMatrix", e2 = "EuclRandMatrix"): Given two Euclidean random matricese1ande2, and an arithmetic operatorop, the Euclidean random matrixe1 op e2is 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 offununder univariate distributions.- E
signature(object = "AbscontDistribution", fun = "EuclRandMatrix", cond = "missing"): expectation offununder absolutely continuous univariate distributions.- E
signature(object = "DiscreteDistribution", fun = "EuclRandMatrix", cond = "missing"): expectation offununder discrete univariate distributions.- E
signature(object = "MultivariateDistribution", fun = "EuclRandMatrix", cond = "missing"): expectation offununder multivariate distributions.- E
signature(object = "DiscreteMVDistribution", fun = "EuclRandMatrix", cond = "missing"): expectation offununder discrete multivariate distributions.- E
signature(object = "UnivariateCondDistribution", fun = "EuclRandMatrix", cond = "numeric"): conditional expectation offununder conditional univariate distributions.- E
signature(object = "AbscontCondDistribution", fun = "EuclRandMatrix", cond = "numeric"): conditional expectation offununder absolutely continuous conditional univariate distributions.- E
signature(object = "DiscreteCondDistribution", fun = "EuclRandMatrix", cond = "numeric"): conditional expectation offununder 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)