[Robast-commits] r1228 - in branches/robast-1.2/pkg/RandVar: . man tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Jan 16 14:38:22 CET 2020
Author: stamats
Date: 2020-01-16 14:38:22 +0100 (Thu, 16 Jan 2020)
New Revision: 1228
Modified:
branches/robast-1.2/pkg/RandVar/DESCRIPTION
branches/robast-1.2/pkg/RandVar/man/0RandVar-package.Rd
branches/robast-1.2/pkg/RandVar/tests/tests.R
branches/robast-1.2/pkg/RandVar/tests/tests.Rout.save
Log:
modified tests as requested by B. Ripley
Modified: branches/robast-1.2/pkg/RandVar/DESCRIPTION
===================================================================
--- branches/robast-1.2/pkg/RandVar/DESCRIPTION 2019-05-13 11:05:26 UTC (rev 1227)
+++ branches/robast-1.2/pkg/RandVar/DESCRIPTION 2020-01-16 13:38:22 UTC (rev 1228)
@@ -1,6 +1,6 @@
Package: RandVar
-Version: 1.2.0
-Date: 2019-04-02
+Version: 1.2.1
+Date: 2020-01-16
Title: Implementation of Random Variables
Description: Implements random variables by means of S4 classes and methods.
Depends: R(>= 3.4), methods, distr(>= 2.8.0), distrEx(>= 2.8.0)
Modified: branches/robast-1.2/pkg/RandVar/man/0RandVar-package.Rd
===================================================================
--- branches/robast-1.2/pkg/RandVar/man/0RandVar-package.Rd 2019-05-13 11:05:26 UTC (rev 1227)
+++ branches/robast-1.2/pkg/RandVar/man/0RandVar-package.Rd 2020-01-16 13:38:22 UTC (rev 1228)
@@ -11,8 +11,8 @@
\details{
\tabular{ll}{
Package: \tab RandVar \cr
-Version: \tab 1.2.0 \cr
-Date: \tab 2019-04-02 \cr
+Version: \tab 1.2.1 \cr
+Date: \tab 2020-01-16 \cr
Depends: \tab R(>= 3.4), methods, distr(>= 2.8.0), distrEx(>= 2.8.0) \cr
Imports: \tab startupmsg \cr
ByteCompile: \tab yes \cr
Modified: branches/robast-1.2/pkg/RandVar/tests/tests.R
===================================================================
--- branches/robast-1.2/pkg/RandVar/tests/tests.R 2019-05-13 11:05:26 UTC (rev 1227)
+++ branches/robast-1.2/pkg/RandVar/tests/tests.R 2020-01-16 13:38:22 UTC (rev 1228)
@@ -1,241 +1,241 @@
-library(RandVar)
-set.seed(123)
-
-###############################################################################
-## start of tests
-###############################################################################
-
-## RandVariable
-(R1 <- new("RandVariable"))
-(R1 <- RandVariable())
-Map(R1)
-Domain(R1)
-Range(R1)
-Map(R1) <- list(function(x){ceiling(x)}, function(x){floor(x)})
-Domain(R1) <- Reals()
-Range(R1) <- Naturals()
-R1
-Map(R1)
-length(R1)
-
-R2 <- R1
-Domain(R2) <- Naturals()
-compatibleDomains(R1, R2)
-Domain(R2) <- NULL
-compatibleDomains(R1, R2)
-Domain(R2) <- EuclideanSpace(dimension = 1)
-compatibleDomains(R1, R2)
-Domain(R2) <- EuclideanSpace(dimension = 2)
-compatibleDomains(R1, R2)
-
-
-## list of functions
-L1 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4})
-L2 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4},
- function(x){x^5}, function(x){x^6})
-L3 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4},
- function(x){x^5}, function(x){x^6}, function(x){x^7}, function(x){x^8})
-L4 <- list(function(x){exp(x)}, function(x){abs(x)},
- function(x){sin(x)}, function(x){floor(x)})
-
-## EuclRandVariable
-(R3 <- new("EuclRandVariable", Map = L4, Domain = Reals(), Range = Reals()))
-(R3 <- EuclRandVariable(L1, Domain = Reals(), dimension = 1))
-Map(R3)
-Range(R3) <- Reals()
-R3[2]
-Map(R3[3])
-Map(R3[c(1,2,4)])
-Map(R3[2:4])
-evalRandVar(R3, rnorm(1))
-x <- as.matrix(rnorm(10))
-res.R3 <- evalRandVar(R3, x)
-res.R3[2,,] # results for Map(R3)[[2]](x)
-res.R3[2,1,] # results for Map(R3)[[2]](x[1,])
-# assuming a probability space with
-# distribution Exp()
-res.R31 <- evalRandVar(R3, x, Gammad())
-res.R31[2,,] # results for Map(R3)[[2]](x)
-res.R31[2,1,] # results for Map(R3)[[2]](x[1,])
-dimension(R3)
-
-R4 <- EuclRandVariable(L4, Domain = Reals(), dimension = 1)
-DL1 <- imageDistr(R4, Norm())
-plot(DL1)
-
-Domain(R4) <- EuclideanSpace(dimension = 2)
-Range(R4) <- EuclideanSpace(dimension = 2)
-(X <- matrix(c(x, rnorm(10)), ncol = 2))
-res2.R4 <- evalRandVar(R4, X)
-res2.R4[3,,1] # results for Map(R4)[[3]](X[,1])
-dimension(R4)
-
-
-## EuclRandMatrix
-(R5 <- as(R4, "EuclRandMatrix"))
-dimension(R5)
-Domain(R5) <- Reals()
-Range(R5) <- Reals()
-(DL2 <- imageDistr(R5, Norm())) # list of distributions
-plot(DL2) # vgl. DL1
-
-Domain(R5) <- EuclideanSpace(dimension = 2)
-Range(R5) <- EuclideanSpace(dimension = 2)
-#res1.R5 <- evalRandVar(R5, rnorm(2))
-#res1.R5[1,1,] # result for map of R5[1,1]
-
-res2.R5 <- evalRandVar(R5, X)
-res2.R5[,,1,2]
-res2.R5[,1,2,1:2]
-res2.R5[1,1,1:2,2]
-
-new("EuclRandMatrix", Map = L2, Dim = as.integer(c(3,2)), Domain = Reals(), Range = Reals())
-(R6 <- EuclRandMatrix(Map = L2, ncol = 2, Domain = Reals(), Range = Reals()))
-R6[1:2, 2]
-R6[1:2, 1:2]
-Map(R6[1,2])
-Map(t(R6)[2,1])
-dimension(R6)
-
-R7 <- EuclRandMatrix(Map = L4, ncol = 2, Domain = Reals(), dimension = 1)
-dimension(R7)
-(DL3 <- imageDistr(R7, Norm()))
-plot(DL3) # vgl. DL1, DL2
-
-
-## EuclRandVarList
-new("EuclRandVarList")
-(RL1 <- EuclRandVarList(R3, R6, R7))
-dimension(RL1)
-as(R4, "EuclRandVarList")
-as(R6, "EuclRandVarList")
-Domain(R5) <- Reals()
-Range(R5) <- Reals()
-(RL2 <- EuclRandVarList(R5, R7))
-(DL4 <- imageDistr(RL2, Norm()))
-plot(DL4)
-
-
-## "Math" group
-system.time(Map(log(abs(R4))), gcFirst = TRUE)
-system.time(Map(gamma(R7)), gcFirst = TRUE)
-system.time(Map(exp(RL1)[[1]]), gcFirst = TRUE)
-
-
-## "Arith" group
-system.time(Map(3 + R3), gcFirst = TRUE)
-Map(c(1,3,5) * R3)
-try(1:5 * R3) # error
-Map(1:2 * R4)
-Map(2/R6)
-Map(c(1,3,5) %% R6)
-Map(R4 - 5)
-Map(R6 %/% 2)
-Map(R3 ^ R3)
-Map(R7 * R7)
-Map((1 + RL1)[[1]])
-Map((RL1 * 2)[[2]])
-system.time(Map((RL1 %% RL1)[[3]]), gcFirst = TRUE)
-
-
-## "%*%"
-M1 <- matrix(1:16, ncol = 8)
-(R8 <- M1 %*% R4)
-Map(R4)
-M1[1,]
-Map(R8)[[1]]
-M1[2,]
-Map(R8)[[2]]
-M2 <- matrix(1:2, ncol = 2)
-(R9 <- M2 %*% R7)
-Map(R7)
-Map(R9)
-Map(1:4 %*% R3) # inner product
-Map(1:2 %*% R7) # corresponds to Map(t(1:2) %*% R7)
-Map(R4 %*% 1:8) # inner product
-Map(R9 %*% 3:4)
-Map(R9 %*% matrix(1:4, nrow = 2))
-(R10 <- R3 %*% matrix(1:16, ncol = 4))
-Map(R10)
-R3 %*% R3 # inner product
-R3 %*% R10
-system.time(R9 %*% R7, gcFirst = TRUE)
-(RL3 <- diag(dimension(RL1)) %*% RL1)
-
-
-## %m% "matrix multiplication" for 'EuclRandVarList'
-system.time(RL4 <- EuclRandVarList(t(R3[1:2]), R7) %m% EuclRandVarList(R6, R9), gcFirst = TRUE)
-
-## integration
-MVD <- DiscreteMVDistribution(supp = matrix(c(r(Pois(5))(10), r(Pois(5))(10)), ncol = 2))
-support(MVD)
-E(MVD)
-E(as(MVD, "MultivariateDistribution"))
-E(MVD, function(x){x})
-E(MVD, function(x){x}, useApply = FALSE)
-E(as(MVD, "MultivariateDistribution"), function(x){x})
-E(as(MVD, "MultivariateDistribution"), function(x){x}, useApply = FALSE)
-E(MVD, function(x){x^2})
-E(as(MVD, "MultivariateDistribution"), function(x){x^2}, useApply = FALSE)
-E(MVD, function(x){x %*% t(x)})
-E(as(MVD, "MultivariateDistribution"), function(x){x %*% t(x)})
-
-R1 <- RealRandVariable(list(function(x){x}, function(x){x^2}), Domain = Reals())
-R2 <- EuclRandMatrix(list(function(x){x}, function(x){x^2}), ncol = 1, Domain = Reals(), dimension = 1)
-E(Norm(), R1)
-E(Norm(), R1, useApply = FALSE)
-E(Norm(), R2)
-E(Norm(), R2, useApply = FALSE)
-R3 <- EuclRandVarList(R1, R2)
-E(Norm(), R3)
-E(Norm(), R3, useApply = FALSE)
-
-R1 <- EuclRandVariable(list(function(x){x}, function(x){x^2}), Domain = EuclideanSpace(2), dimension = 2)
-R2 <- EuclRandMatrix(list(function(x){x}, function(x){x^2}), ncol = 1, Domain = EuclideanSpace(2), dimension = 2)
-E(MVD, R1)
-E(MVD, R1, useApply = FALSE)
-E(MVD, R2)[1:2,,]
-E(MVD, R2, useApply = FALSE)[1:2,,]
-R3 <- EuclRandVarList(R1, R2)
-E1 <- E(MVD, R3)
-E1[[1]]
-E1[[2]][1:2,,]
-E(MVD, R3, useApply = FALSE)
-
-CD <- LMCondDistribution(theta = 1)
-E(CD, cond = 2)
-E(CD, cond = 2, useApply = FALSE)
-E(CD, function(x){x}, cond = 2)
-E(CD, function(x){x}, cond = 2, useApply = FALSE)
-E(CD, function(x, cond){2*x}, cond = 2, withCond = FALSE)
-E(CD, function(x, cond){2*x}, cond = 2, withCond = TRUE, useApply = FALSE)
-E(CD, function(x){x^2}, cond = 2)
-E(CD, function(x){x^2}, cond = 2, useApply = FALSE)
-E(CD, function(x, cond){x^2*cond}, cond = 2, withCond = TRUE)
-E(CD, function(x, cond){x^2*cond}, cond = 2, withCond = TRUE, useApply = FALSE)
-Range(R1) <- Reals()
-Domain(R1) <- Reals()
-E(CD, R1, cond = 2)
-E(CD, R1, cond = 2, useApply = FALSE)
-R3 <- EuclRandVariable(list(function(x){x[2]*x[1]}, function(x){x[2]*x[1]^2}),
- Domain = EuclideanSpace(2), dimension = 1)
-E(CD, R3, cond = 2, withCond = TRUE)
-Range(R2) <- Reals()
-Domain(R2) <- Reals()
-E(CD, R2, cond = 2)
-E(CD, R2, cond = 2, useApply = FALSE)
-R4 <- EuclRandMatrix(list(function(x){x[2]*x[1]}, function(x){x[2]*x[1]^2}),
- ncol = 1, Domain = EuclideanSpace(2), dimension = 1)
-E(CD, R4, cond = 2, withCond = TRUE)
-R5 <- EuclRandVarList(R1, R2)
-E(CD, R5, cond = 2)
-E(CD, R5, cond = 2, useApply = FALSE)
-R6 <- EuclRandVarList(R3, R4)
-E(CD, R6, cond = 2, withCond = TRUE)
-
-
-###############################################################################
-## end of tests
-###############################################################################
-
-q("no")
+library(RandVar)
+set.seed(123)
+
+###############################################################################
+## start of tests
+###############################################################################
+
+## RandVariable
+(R1 <- new("RandVariable"))
+(R1 <- RandVariable())
+Map(R1)
+Domain(R1)
+Range(R1)
+Map(R1) <- list(function(x){ceiling(x)}, function(x){floor(x)})
+Domain(R1) <- Reals()
+Range(R1) <- Naturals()
+R1
+Map(R1)
+length(R1)
+
+R2 <- R1
+Domain(R2) <- Naturals()
+compatibleDomains(R1, R2)
+Domain(R2) <- NULL
+compatibleDomains(R1, R2)
+Domain(R2) <- EuclideanSpace(dimension = 1)
+compatibleDomains(R1, R2)
+Domain(R2) <- EuclideanSpace(dimension = 2)
+compatibleDomains(R1, R2)
+
+
+## list of functions
+L1 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4})
+L2 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4},
+ function(x){x^5}, function(x){x^6})
+L3 <- list(function(x){x}, function(x){x^2}, function(x){x^3}, function(x){x^4},
+ function(x){x^5}, function(x){x^6}, function(x){x^7}, function(x){x^8})
+L4 <- list(function(x){exp(x)}, function(x){abs(x)},
+ function(x){sin(x)}, function(x){floor(x)})
+
+## EuclRandVariable
+(R3 <- new("EuclRandVariable", Map = L4, Domain = Reals(), Range = Reals()))
+(R3 <- EuclRandVariable(L1, Domain = Reals(), dimension = 1))
+Map(R3)
+Range(R3) <- Reals()
+R3[2]
+Map(R3[3])
+Map(R3[c(1,2,4)])
+Map(R3[2:4])
+evalRandVar(R3, rnorm(1))
+x <- as.matrix(rnorm(10))
+res.R3 <- evalRandVar(R3, x)
+res.R3[2,,] # results for Map(R3)[[2]](x)
+res.R3[2,1,] # results for Map(R3)[[2]](x[1,])
+# assuming a probability space with
+# distribution Exp()
+res.R31 <- evalRandVar(R3, x, Gammad())
+res.R31[2,,] # results for Map(R3)[[2]](x)
+res.R31[2,1,] # results for Map(R3)[[2]](x[1,])
+dimension(R3)
+
+R4 <- EuclRandVariable(L4, Domain = Reals(), dimension = 1)
+DL1 <- imageDistr(R4, Norm())
+plot(DL1)
+
+Domain(R4) <- EuclideanSpace(dimension = 2)
+Range(R4) <- EuclideanSpace(dimension = 2)
+(X <- matrix(c(x, rnorm(10)), ncol = 2))
+res2.R4 <- evalRandVar(R4, X)
+res2.R4[3,,1] # results for Map(R4)[[3]](X[,1])
+dimension(R4)
+
+
+## EuclRandMatrix
+(R5 <- as(R4, "EuclRandMatrix"))
+dimension(R5)
+Domain(R5) <- Reals()
+Range(R5) <- Reals()
+(DL2 <- imageDistr(R5, Norm())) # list of distributions
+plot(DL2) # vgl. DL1
+
+Domain(R5) <- EuclideanSpace(dimension = 2)
+Range(R5) <- EuclideanSpace(dimension = 2)
+#res1.R5 <- evalRandVar(R5, rnorm(2))
+#res1.R5[1,1,] # result for map of R5[1,1]
+
+res2.R5 <- evalRandVar(R5, X)
+res2.R5[,,1,2]
+res2.R5[,1,2,1:2]
+res2.R5[1,1,1:2,2]
+
+new("EuclRandMatrix", Map = L2, Dim = as.integer(c(3,2)), Domain = Reals(), Range = Reals())
+(R6 <- EuclRandMatrix(Map = L2, ncol = 2, Domain = Reals(), Range = Reals()))
+R6[1:2, 2]
+R6[1:2, 1:2]
+Map(R6[1,2])
+Map(t(R6)[2,1])
+dimension(R6)
+
+R7 <- EuclRandMatrix(Map = L4, ncol = 2, Domain = Reals(), dimension = 1)
+dimension(R7)
+(DL3 <- imageDistr(R7, Norm()))
+plot(DL3) # vgl. DL1, DL2
+
+
+## EuclRandVarList
+new("EuclRandVarList")
+(RL1 <- EuclRandVarList(R3, R6, R7))
+dimension(RL1)
+as(R4, "EuclRandVarList")
+as(R6, "EuclRandVarList")
+Domain(R5) <- Reals()
+Range(R5) <- Reals()
+(RL2 <- EuclRandVarList(R5, R7))
+(DL4 <- imageDistr(RL2, Norm()))
+plot(DL4)
+
+
+## "Math" group
+Map(log(abs(R4)))
+Map(gamma(R7))
+Map(exp(RL1)[[1]])
+
+
+## "Arith" group
+Map(3 + R3)
+Map(c(1,3,5) * R3)
+try(1:5 * R3) # error
+Map(1:2 * R4)
+Map(2/R6)
+Map(c(1,3,5) %% R6)
+Map(R4 - 5)
+Map(R6 %/% 2)
+Map(R3 ^ R3)
+Map(R7 * R7)
+Map((1 + RL1)[[1]])
+Map((RL1 * 2)[[2]])
+Map((RL1 %% RL1)[[3]])
+
+
+## "%*%"
+M1 <- matrix(1:16, ncol = 8)
+(R8 <- M1 %*% R4)
+Map(R4)
+M1[1,]
+Map(R8)[[1]]
+M1[2,]
+Map(R8)[[2]]
+M2 <- matrix(1:2, ncol = 2)
+(R9 <- M2 %*% R7)
+Map(R7)
+Map(R9)
+Map(1:4 %*% R3) # inner product
+Map(1:2 %*% R7) # corresponds to Map(t(1:2) %*% R7)
+Map(R4 %*% 1:8) # inner product
+Map(R9 %*% 3:4)
+Map(R9 %*% matrix(1:4, nrow = 2))
+(R10 <- R3 %*% matrix(1:16, ncol = 4))
+Map(R10)
+R3 %*% R3 # inner product
+R3 %*% R10
+R9 %*% R7
+(RL3 <- diag(dimension(RL1)) %*% RL1)
+
+
+## %m% "matrix multiplication" for 'EuclRandVarList'
+RL4 <- EuclRandVarList(t(R3[1:2]), R7) %m% EuclRandVarList(R6, R9)
+
+## integration
+MVD <- DiscreteMVDistribution(supp = matrix(c(r(Pois(5))(10), r(Pois(5))(10)), ncol = 2))
+support(MVD)
+E(MVD)
+E(as(MVD, "MultivariateDistribution"))
+E(MVD, function(x){x})
+E(MVD, function(x){x}, useApply = FALSE)
+E(as(MVD, "MultivariateDistribution"), function(x){x})
+E(as(MVD, "MultivariateDistribution"), function(x){x}, useApply = FALSE)
+E(MVD, function(x){x^2})
+E(as(MVD, "MultivariateDistribution"), function(x){x^2}, useApply = FALSE)
+E(MVD, function(x){x %*% t(x)})
+E(as(MVD, "MultivariateDistribution"), function(x){x %*% t(x)})
+
+R1 <- RealRandVariable(list(function(x){x}, function(x){x^2}), Domain = Reals())
+R2 <- EuclRandMatrix(list(function(x){x}, function(x){x^2}), ncol = 1, Domain = Reals(), dimension = 1)
+E(Norm(), R1)
+E(Norm(), R1, useApply = FALSE)
+E(Norm(), R2)
+E(Norm(), R2, useApply = FALSE)
+R3 <- EuclRandVarList(R1, R2)
+E(Norm(), R3)
+E(Norm(), R3, useApply = FALSE)
+
+R1 <- EuclRandVariable(list(function(x){x}, function(x){x^2}), Domain = EuclideanSpace(2), dimension = 2)
+R2 <- EuclRandMatrix(list(function(x){x}, function(x){x^2}), ncol = 1, Domain = EuclideanSpace(2), dimension = 2)
+E(MVD, R1)
+E(MVD, R1, useApply = FALSE)
+E(MVD, R2)[1:2,,]
+E(MVD, R2, useApply = FALSE)[1:2,,]
+R3 <- EuclRandVarList(R1, R2)
+E1 <- E(MVD, R3)
+E1[[1]]
+E1[[2]][1:2,,]
+E(MVD, R3, useApply = FALSE)
+
+CD <- LMCondDistribution(theta = 1)
+E(CD, cond = 2)
+E(CD, cond = 2, useApply = FALSE)
+E(CD, function(x){x}, cond = 2)
+E(CD, function(x){x}, cond = 2, useApply = FALSE)
+E(CD, function(x, cond){2*x}, cond = 2, withCond = FALSE)
+E(CD, function(x, cond){2*x}, cond = 2, withCond = TRUE, useApply = FALSE)
+E(CD, function(x){x^2}, cond = 2)
+E(CD, function(x){x^2}, cond = 2, useApply = FALSE)
+E(CD, function(x, cond){x^2*cond}, cond = 2, withCond = TRUE)
+E(CD, function(x, cond){x^2*cond}, cond = 2, withCond = TRUE, useApply = FALSE)
+Range(R1) <- Reals()
+Domain(R1) <- Reals()
+E(CD, R1, cond = 2)
+E(CD, R1, cond = 2, useApply = FALSE)
+R3 <- EuclRandVariable(list(function(x){x[2]*x[1]}, function(x){x[2]*x[1]^2}),
+ Domain = EuclideanSpace(2), dimension = 1)
+E(CD, R3, cond = 2, withCond = TRUE)
+Range(R2) <- Reals()
+Domain(R2) <- Reals()
+E(CD, R2, cond = 2)
+E(CD, R2, cond = 2, useApply = FALSE)
+R4 <- EuclRandMatrix(list(function(x){x[2]*x[1]}, function(x){x[2]*x[1]^2}),
+ ncol = 1, Domain = EuclideanSpace(2), dimension = 1)
+E(CD, R4, cond = 2, withCond = TRUE)
+R5 <- EuclRandVarList(R1, R2)
+E(CD, R5, cond = 2)
+E(CD, R5, cond = 2, useApply = FALSE)
+R6 <- EuclRandVarList(R3, R4)
+E(CD, R6, cond = 2, withCond = TRUE)
+
+
+###############################################################################
+## end of tests
+###############################################################################
+
+q("no")
Modified: branches/robast-1.2/pkg/RandVar/tests/tests.Rout.save
===================================================================
--- branches/robast-1.2/pkg/RandVar/tests/tests.Rout.save 2019-05-13 11:05:26 UTC (rev 1227)
+++ branches/robast-1.2/pkg/RandVar/tests/tests.Rout.save 2020-01-16 13:38:22 UTC (rev 1228)
@@ -1,6 +1,6 @@
-R version 3.5.3 RC (2019-03-04 r76204) -- "Great Truth"
-Copyright (C) 2019 The R Foundation for Statistical Computing
+R version 3.6.2 Patched (2020-01-03 r77636) -- "Dark and Stormy Night"
+Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -74,7 +74,7 @@
IQR, mad, median, var
-:RandVar> Implementation of Random Variables (version 1.2.0)
+:RandVar> Implementation of Random Variables (version 1.2.1)
:RandVar>
:RandVar> For more information see ?"RandVar", NEWS("RandVar"), as
:RandVar> well as
@@ -104,7 +104,7 @@
function (x)
{
}
-<environment: 0x55a85c0>
+<environment: 0x56370ab5b4d0>
> Domain(R1)
NULL
@@ -312,10 +312,10 @@
[[3]] Distribution Object of Class: AbscontDistribution
[[4]] Distribution Object of Class: AbscontDistribution
Warning messages:
-1: In new("standardGeneric", .Data = function (object) :
+1: In (new("standardGeneric", .Data = function (object) :
arithmetics on distributions are understood as operations on r.v.'s
see 'distrARITH()'; for switching off this warning see '?distroptions'
-2: In new("standardGeneric", .Data = function (object) :
+2: In (new("standardGeneric", .Data = function (object) :
slots d,p,q have been filled using simulations; for switching off this warning see '?distroptions'
> plot(DL2) # vgl. DL1
>
@@ -373,7 +373,7 @@
}
t(f(x))
}
-<environment: 0x9bb3fd0>
+<environment: 0x56370ed10f20>
> dimension(R6)
[1] 6
@@ -388,10 +388,10 @@
[[3]] Distribution Object of Class: AbscontDistribution
[[4]] Distribution Object of Class: AbscontDistribution
Warning messages:
-1: In new("standardGeneric", .Data = function (object) :
+1: In (new("standardGeneric", .Data = function (object) :
arithmetics on distributions are understood as operations on r.v.'s
see 'distrARITH()'; for switching off this warning see '?distroptions'
-2: In new("standardGeneric", .Data = function (object) :
+2: In (new("standardGeneric", .Data = function (object) :
slots d,p,q have been filled using simulations; for switching off this warning see '?distroptions'
> plot(DL3) # vgl. DL1, DL2
>
@@ -451,30 +451,214 @@
[[7]] Distribution Object of Class: AbscontDistribution
[[8]] Distribution Object of Class: AbscontDistribution
Warning messages:
-1: In new("standardGeneric", .Data = function (object) :
+1: In (new("standardGeneric", .Data = function (object) :
arithmetics on distributions are understood as operations on r.v.'s
see 'distrARITH()'; for switching off this warning see '?distroptions'
-2: In new("standardGeneric", .Data = function (object) :
+2: In (new("standardGeneric", .Data = function (object) :
slots d,p,q have been filled using simulations; for switching off this warning see '?distroptions'
> plot(DL4)
>
>
> ## "Math" group
-> system.time(Map(log(abs(R4))), gcFirst = TRUE)
- user system elapsed
- 0.000 0.000 0.001
-> system.time(Map(gamma(R7)), gcFirst = TRUE)
- user system elapsed
- 0.001 0.000 0.001
-> system.time(Map(exp(RL1)[[1]]), gcFirst = TRUE)
- user system elapsed
- 0.001 0.000 0.001
+> Map(log(abs(R4)))
+[[1]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ f1 <- function (x)
+ {
+ exp(x)
+ }
+ abs(f1(x))
+ }
+ log(f1(x))
+}
+<environment: 0x56370d3d86c8>
+
+[[2]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ f1 <- function (x)
+ {
+ abs(x)
+ }
+ abs(f1(x))
+ }
+ log(f1(x))
+}
+<environment: 0x56370d3d86c8>
+
+[[3]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ f1 <- function (x)
+ {
+ sin(x)
+ }
+ abs(f1(x))
+ }
+ log(f1(x))
+}
+<environment: 0x56370d3d86c8>
+
+[[4]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ f1 <- function (x)
+ {
+ floor(x)
+ }
+ abs(f1(x))
+ }
+ log(f1(x))
+}
+<environment: 0x56370d3d86c8>
+
+> Map(gamma(R7))
+[[1]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ exp(x)
+ }
+ gamma(f1(x))
+}
+<environment: 0x563710782428>
+
+[[2]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ abs(x)
+ }
+ gamma(f1(x))
+}
+<environment: 0x563710782428>
+
+[[3]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ sin(x)
+ }
+ gamma(f1(x))
+}
+<environment: 0x563710782428>
+
+[[4]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ floor(x)
+ }
+ gamma(f1(x))
+}
+<environment: 0x563710782428>
+
+> Map(exp(RL1)[[1]])
+[[1]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ x
+ }
+ exp(f1(x))
+}
+<environment: 0x56370f35f2d8>
+
+[[2]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ x^2
+ }
+ exp(f1(x))
+}
+<environment: 0x56370f35f2d8>
+
+[[3]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ x^3
+ }
+ exp(f1(x))
+}
+<environment: 0x56370f35f2d8>
+
+[[4]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ x^4
+ }
+ exp(f1(x))
+}
+<environment: 0x56370f35f2d8>
+
>
>
> ## "Arith" group
-> system.time(Map(3 + R3), gcFirst = TRUE)
- user system elapsed
- 0.000 0.000 0.001
+> Map(3 + R3)
+[[1]]
+function (x)
+{
+ f2 <- function (x)
+ {
+ x
+ }
+ 3 + f2(x)
+}
+<environment: 0x56370cf1f060>
+
+[[2]]
+function (x)
+{
+ f2 <- function (x)
+ {
+ x^2
+ }
+ 3 + f2(x)
+}
+<environment: 0x56370cf1f060>
+
+[[3]]
+function (x)
+{
+ f2 <- function (x)
+ {
+ x^3
+ }
+ 3 + f2(x)
+}
+<environment: 0x56370cf1f060>
+
+[[4]]
+function (x)
+{
+ f2 <- function (x)
+ {
+ x^4
+ }
+ 3 + f2(x)
+}
+<environment: 0x56370cf1f060>
+
> Map(c(1,3,5) * R3)
[[1]]
function (x)
@@ -485,7 +669,7 @@
}
1 * f2(x)
}
-<environment: 0xc3f3fe8>
+<environment: 0x56370d14d468>
[[2]]
function (x)
@@ -496,7 +680,7 @@
}
3 * f2(x)
}
-<environment: 0xc3f3fe8>
+<environment: 0x56370d14d468>
[[3]]
function (x)
@@ -507,7 +691,7 @@
}
5 * f2(x)
}
-<environment: 0xc3f3fe8>
+<environment: 0x56370d14d468>
[[4]]
function (x)
@@ -518,7 +702,7 @@
}
1 * f2(x)
}
-<environment: 0xc3f3fe8>
+<environment: 0x56370d14d468>
Warning message:
In c(1, 3, 5) * R3 :
@@ -536,7 +720,7 @@
}
1:2 * f2(x)
}
-<environment: 0xc16a660>
+<environment: 0x56370d777838>
[[2]]
function (x)
@@ -547,7 +731,7 @@
}
1:2 * f2(x)
}
-<environment: 0xc16a660>
+<environment: 0x56370d777838>
[[3]]
function (x)
@@ -558,7 +742,7 @@
}
1:2 * f2(x)
}
-<environment: 0xc16a660>
+<environment: 0x56370d777838>
[[4]]
function (x)
@@ -569,7 +753,7 @@
}
1:2 * f2(x)
}
-<environment: 0xc16a660>
+<environment: 0x56370d777838>
> Map(2/R6)
[[1]]
@@ -581,7 +765,7 @@
}
2/f2(x)
}
-<environment: 0xc076510>
+<environment: 0x56370e20c818>
[[2]]
function (x)
@@ -592,7 +776,7 @@
}
2/f2(x)
}
-<environment: 0xc076510>
+<environment: 0x56370e20c818>
[[3]]
function (x)
@@ -603,7 +787,7 @@
}
2/f2(x)
}
-<environment: 0xc076510>
+<environment: 0x56370e20c818>
[[4]]
function (x)
@@ -614,7 +798,7 @@
}
2/f2(x)
}
-<environment: 0xc076510>
+<environment: 0x56370e20c818>
[[5]]
function (x)
@@ -625,7 +809,7 @@
}
2/f2(x)
}
-<environment: 0xc076510>
+<environment: 0x56370e20c818>
[[6]]
function (x)
@@ -636,7 +820,7 @@
}
2/f2(x)
}
-<environment: 0xc076510>
+<environment: 0x56370e20c818>
> Map(c(1,3,5) %% R6)
[[1]]
@@ -648,7 +832,7 @@
}
1%%f2(x)
}
-<environment: 0xbfbdac8>
+<environment: 0x56370ef7df40>
[[2]]
function (x)
@@ -659,7 +843,7 @@
}
3%%f2(x)
}
-<environment: 0xbfbdac8>
+<environment: 0x56370ef7df40>
[[3]]
function (x)
@@ -670,7 +854,7 @@
}
5%%f2(x)
}
-<environment: 0xbfbdac8>
+<environment: 0x56370ef7df40>
[[4]]
function (x)
@@ -681,7 +865,7 @@
}
1%%f2(x)
}
-<environment: 0xbfbdac8>
+<environment: 0x56370ef7df40>
[[5]]
function (x)
@@ -692,7 +876,7 @@
}
3%%f2(x)
}
-<environment: 0xbfbdac8>
+<environment: 0x56370ef7df40>
[[6]]
function (x)
@@ -703,7 +887,7 @@
}
5%%f2(x)
}
-<environment: 0xbfbdac8>
+<environment: 0x56370ef7df40>
> Map(R4 - 5)
[[1]]
@@ -715,7 +899,7 @@
}
f1(x) - c(5, 5)
}
-<environment: 0xbf68e78>
+<environment: 0x56370e3d3dd0>
[[2]]
function (x)
@@ -726,7 +910,7 @@
}
f1(x) - c(5, 5)
}
-<environment: 0xbf68e78>
+<environment: 0x56370e3d3dd0>
[[3]]
function (x)
@@ -737,7 +921,7 @@
}
f1(x) - c(5, 5)
}
-<environment: 0xbf68e78>
+<environment: 0x56370e3d3dd0>
[[4]]
function (x)
@@ -748,7 +932,7 @@
}
f1(x) - c(5, 5)
}
-<environment: 0xbf68e78>
+<environment: 0x56370e3d3dd0>
> Map(R6 %/% 2)
[[1]]
@@ -760,7 +944,7 @@
}
f1(x)%/%2
}
-<environment: 0xbecdee0>
+<environment: 0x56370dbe5ad0>
[[2]]
function (x)
@@ -771,7 +955,7 @@
}
f1(x)%/%2
}
-<environment: 0xbecdee0>
+<environment: 0x56370dbe5ad0>
[[3]]
function (x)
@@ -782,7 +966,7 @@
}
f1(x)%/%2
}
-<environment: 0xbecdee0>
+<environment: 0x56370dbe5ad0>
[[4]]
function (x)
@@ -793,7 +977,7 @@
}
f1(x)%/%2
}
-<environment: 0xbecdee0>
+<environment: 0x56370dbe5ad0>
[[5]]
function (x)
@@ -804,7 +988,7 @@
}
f1(x)%/%2
}
-<environment: 0xbecdee0>
+<environment: 0x56370dbe5ad0>
[[6]]
function (x)
@@ -815,7 +999,7 @@
}
f1(x)%/%2
}
-<environment: 0xbecdee0>
+<environment: 0x56370dbe5ad0>
> Map(R3 ^ R3)
[[1]]
@@ -831,7 +1015,7 @@
}
f1(x)^f2(x)
}
-<environment: 0xbe780a8>
+<environment: 0x56370eebe9b8>
[[2]]
function (x)
@@ -846,7 +1030,7 @@
}
f1(x)^f2(x)
}
-<environment: 0xbe780a8>
+<environment: 0x56370eebe9b8>
[[3]]
function (x)
@@ -861,7 +1045,7 @@
}
f1(x)^f2(x)
}
-<environment: 0xbe780a8>
+<environment: 0x56370eebe9b8>
[[4]]
function (x)
@@ -876,7 +1060,7 @@
}
f1(x)^f2(x)
}
-<environment: 0xbe780a8>
+<environment: 0x56370eebe9b8>
> Map(R7 * R7)
[[1]]
@@ -892,7 +1076,7 @@
}
f1(x) * f2(x)
}
-<environment: 0xbd96ee8>
+<environment: 0x56370e33a5f8>
[[2]]
function (x)
@@ -907,7 +1091,7 @@
}
f1(x) * f2(x)
}
-<environment: 0xbd96ee8>
+<environment: 0x56370e33a5f8>
[[3]]
function (x)
@@ -922,7 +1106,7 @@
}
f1(x) * f2(x)
}
-<environment: 0xbd96ee8>
+<environment: 0x56370e33a5f8>
[[4]]
function (x)
@@ -937,7 +1121,7 @@
}
f1(x) * f2(x)
}
-<environment: 0xbd96ee8>
+<environment: 0x56370e33a5f8>
> Map((1 + RL1)[[1]])
[[1]]
@@ -949,7 +1133,7 @@
}
1 + f2(x)
}
-<environment: 0xbd32ea8>
+<environment: 0x56370f4d8260>
[[2]]
function (x)
@@ -960,7 +1144,7 @@
}
1 + f2(x)
}
-<environment: 0xbd32ea8>
+<environment: 0x56370f4d8260>
[[3]]
function (x)
@@ -971,7 +1155,7 @@
}
1 + f2(x)
}
-<environment: 0xbd32ea8>
+<environment: 0x56370f4d8260>
[[4]]
function (x)
@@ -982,7 +1166,7 @@
}
1 + f2(x)
}
-<environment: 0xbd32ea8>
+<environment: 0x56370f4d8260>
> Map((RL1 * 2)[[2]])
[[1]]
@@ -994,7 +1178,7 @@
}
f1(x) * 2
}
-<environment: 0xbb99f30>
+<environment: 0x56370c977998>
[[2]]
function (x)
@@ -1005,7 +1189,7 @@
}
f1(x) * 2
}
-<environment: 0xbb99f30>
+<environment: 0x56370c977998>
[[3]]
function (x)
@@ -1016,7 +1200,7 @@
}
f1(x) * 2
}
-<environment: 0xbb99f30>
+<environment: 0x56370c977998>
[[4]]
function (x)
@@ -1027,7 +1211,7 @@
}
f1(x) * 2
}
-<environment: 0xbb99f30>
+<environment: 0x56370c977998>
[[5]]
function (x)
@@ -1038,7 +1222,7 @@
}
f1(x) * 2
}
-<environment: 0xbb99f30>
+<environment: 0x56370c977998>
[[6]]
function (x)
@@ -1049,11 +1233,69 @@
}
f1(x) * 2
}
-<environment: 0xbb99f30>
+<environment: 0x56370c977998>
-> system.time(Map((RL1 %% RL1)[[3]]), gcFirst = TRUE)
- user system elapsed
- 0.001 0.000 0.002
+> Map((RL1 %% RL1)[[3]])
+[[1]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ exp(x)
+ }
+ f2 <- function (x)
+ {
+ exp(x)
+ }
+ f1(x)%%f2(x)
+}
+<environment: 0x56370d7acc50>
+
+[[2]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ abs(x)
+ }
+ f2 <- function (x)
+ {
+ abs(x)
+ }
+ f1(x)%%f2(x)
+}
+<environment: 0x56370d7acc50>
+
+[[3]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ sin(x)
+ }
+ f2 <- function (x)
+ {
+ sin(x)
+ }
+ f1(x)%%f2(x)
+}
+<environment: 0x56370d7acc50>
+
+[[4]]
+function (x)
+{
+ f1 <- function (x)
+ {
+ floor(x)
+ }
+ f2 <- function (x)
+ {
+ floor(x)
+ }
+ f1(x)%%f2(x)
+}
+<environment: 0x56370d7acc50>
+
>
>
> ## "%*%"
@@ -1069,7 +1311,7 @@
{
exp(x)
}
-<bytecode: 0x6de9858>
+<bytecode: 0x56370e1be998>
[[2]]
function (x)
@@ -1076,7 +1318,7 @@
{
abs(x)
}
-<bytecode: 0x6ccebc8>
+<bytecode: 0x56370c024de8>
[[3]]
function (x)
@@ -1083,7 +1325,7 @@
{
sin(x)
}
-<bytecode: 0x6a427d8>
+<bytecode: 0x563708678e90>
[[4]]
function (x)
@@ -1090,7 +1332,7 @@
{
floor(x)
}
-<bytecode: 0x687f070>
+<bytecode: 0x56370bf8cd88>
> M1[1,]
[1] 1 3 5 7 9 11 13 15
@@ -1127,7 +1369,7 @@
}
f1(x) + c(13L, 15L) %*% f2(x)
}
-<environment: 0xc065a60>
+<environment: 0x56370df1b5d8>
> M1[2,]
[1] 2 4 6 8 10 12 14 16
> Map(R8)[[2]]
@@ -1163,7 +1405,7 @@
}
f1(x) + c(14L, 16L) %*% f2(x)
}
-<environment: 0xc065a60>
+<environment: 0x56370df1b5d8>
> M2 <- matrix(1:2, ncol = 2)
> (R9 <- M2 %*% R7)
An object of class "EuclRandMatrix"
@@ -1176,7 +1418,7 @@
{
exp(x)
}
-<bytecode: 0x6de9858>
+<bytecode: 0x56370e1be998>
[[2]]
function (x)
@@ -1183,7 +1425,7 @@
{
abs(x)
}
-<bytecode: 0x6ccebc8>
+<bytecode: 0x56370c024de8>
[[3]]
function (x)
@@ -1190,7 +1432,7 @@
{
sin(x)
}
-<bytecode: 0x6a427d8>
+<bytecode: 0x563708678e90>
[[4]]
function (x)
@@ -1197,7 +1439,7 @@
{
floor(x)
}
-<bytecode: 0x687f070>
+<bytecode: 0x56370bf8cd88>
> Map(R9)
[[1]]
@@ -1217,7 +1459,7 @@
}
f1(x) + 2L %*% f2(x)
}
-<environment: 0xbf016d0>
+<environment: 0x56370b7429a8>
[[2]]
function (x)
@@ -1236,7 +1478,7 @@
}
f1(x) + 2L %*% f2(x)
}
-<environment: 0xbe72b18>
+<environment: 0x56370d74fc50>
> Map(1:4 %*% R3) # inner product
[[1]]
@@ -1272,7 +1514,7 @@
}
f1(x) + 4L %*% f2(x)
}
-<environment: 0xbd9da38>
+<environment: 0x56370c86b3f0>
> Map(1:2 %*% R7) # corresponds to Map(t(1:2) %*% R7)
[[1]]
@@ -1292,7 +1534,7 @@
}
f1(x) + 2L %*% f2(x)
}
-<environment: 0xbccb498>
+<environment: 0x56370b875c98>
[[2]]
function (x)
@@ -1311,7 +1553,7 @@
}
f1(x) + 2L %*% f2(x)
}
-<environment: 0xbc55ab8>
+<environment: 0x56370d40f270>
> Map(R4 %*% 1:8) # inner product
[[1]]
@@ -1383,7 +1625,7 @@
}
t(f(x))
}
-<environment: 0xbadaf38>
+<environment: 0x56370c819b60>
> Map(R9 %*% 3:4)
[[1]]
@@ -1439,7 +1681,7 @@
}
t(f(x))
}
-<environment: 0xba1fa98>
+<environment: 0x56370f09cd20>
> Map(R9 %*% matrix(1:4, nrow = 2))
[[1]]
@@ -1495,7 +1737,7 @@
}
t(f(x))
}
-<environment: 0xb9070d0>
+<environment: 0x56371139a410>
[[2]]
function (x)
@@ -1550,7 +1792,7 @@
}
t(f(x))
}
-<environment: 0xb9070d0>
+<environment: 0x56371139a410>
> (R10 <- R3 %*% matrix(1:16, ncol = 4))
An object of class "EuclRandMatrix"
@@ -1595,7 +1837,7 @@
}
t(f(x))
}
-<environment: 0xb7ade38>
+<environment: 0x56370e6201c0>
[[2]]
function (x)
@@ -1634,7 +1876,7 @@
}
t(f(x))
}
-<environment: 0xb7ade38>
+<environment: 0x56370e6201c0>
[[3]]
function (x)
@@ -1673,7 +1915,7 @@
}
t(f(x))
}
-<environment: 0xb7ade38>
+<environment: 0x56370e6201c0>
[[4]]
function (x)
@@ -1712,7 +1954,7 @@
}
t(f(x))
}
-<environment: 0xb7ade38>
+<environment: 0x56370e6201c0>
> R3 %*% R3 # inner product
An object of class "EuclRandMatrix"
@@ -1724,9 +1966,11 @@
Dim of Map: 4 4
Domain: Real Space with dimension 1
Range: Euclidean Space with dimension 1
-> system.time(R9 %*% R7, gcFirst = TRUE)
- user system elapsed
- 0.001 0.000 0.001
+> R9 %*% R7
+An object of class "EuclRandMatrix"
+Dim of Map: 1 2
+Domain: Real Space with dimension 1
+Range: Euclidean Space with dimension 1
> (RL3 <- diag(dimension(RL1)) %*% RL1)
An object of class "EuclRandMatrix"
Dim of Map: 14 1
@@ -1735,9 +1979,7 @@
>
>
> ## %m% "matrix multiplication" for 'EuclRandVarList'
-> system.time(RL4 <- EuclRandVarList(t(R3[1:2]), R7) %m% EuclRandVarList(R6, R9), gcFirst = TRUE)
- user system elapsed
- 0.008 0.000 0.008
+> RL4 <- EuclRandVarList(t(R3[1:2]), R7) %m% EuclRandVarList(R6, R9)
>
> ## integration
> MVD <- DiscreteMVDistribution(supp = matrix(c(r(Pois(5))(10), r(Pois(5))(10)), ncol = 2))
@@ -1948,4 +2190,4 @@
> q("no")
> proc.time()
user system elapsed
- 4.835 0.068 4.896
+ 3.291 0.099 3.384
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