[Yuima-commits] r714 - / .Rproj.user .Rproj.user/A3842A2 .Rproj.user/A3842A2/console06 .Rproj.user/A3842A2/pcs .Rproj.user/A3842A2/sources .Rproj.user/A3842A2/sources/per .Rproj.user/A3842A2/sources/per/t .Rproj.user/A3842A2/sources/prop .Rproj.user/shared .Rproj.user/shared/notebooks R data inst inst/ybook man src
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sun Sep 22 22:36:43 CEST 2019
Author: phoenix844
Date: 2019-09-22 22:36:42 +0200 (Sun, 22 Sep 2019)
New Revision: 714
Added:
.Rbuildignore
.Rhistory
.Rproj.user/
.Rproj.user/A3842A2/
.Rproj.user/A3842A2/console06/
.Rproj.user/A3842A2/console06/INDEX001
.Rproj.user/A3842A2/cpp-complilation-config
.Rproj.user/A3842A2/cpp-definition-cache
.Rproj.user/A3842A2/ctx/
.Rproj.user/A3842A2/explorer-cache/
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.Rproj.user/A3842A2/pcs/debug-breakpoints.pper
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.Rproj.user/shared/notebooks/
.Rproj.user/shared/notebooks/patch-chunk-names
.Rproj.user/shared/notebooks/paths
COPYING
DESCRIPTION
NAMESPACE
NEWS
R/
R/.Rhistory
R/AllClasses.R
R/AuxMethodforPPR.R
R/CPoint.R
R/CarmaNoise.R
R/CholeskyfGn.R
R/ClassCogarch.R
R/DataPPR.R
R/DiagnosticCarma.R
R/DiagnosticCogarch.R
R/FunctionAndOperators.R
R/IC.R
R/MM.COGARCH.R
R/MethodForLaw.R
R/NewClasses.R
R/PointProcessClasses.R
R/PseudoLogLikCOGARCH.R
R/RcppExports.R
R/WoodChanfGn.R
R/adaBayes.R
R/asymptotic_term_second.R
R/asymptotic_term_third.R
R/asymptotic_term_third_function.R
R/bns.test.R
R/cce.R
R/cogarchNoise.R
R/hyavar.R
R/lambdaPPR.R
R/lasso.R
R/limiting.gamma.R
R/llag.R
R/llag.test.R
R/lse.R
R/lseBayes.R
R/mllag.R
R/mmfrac.R
R/mpv.R
R/noisy.sampling.R
R/phi.test.R
R/poisson.random.sampling.R
R/qgv.R
R/qmle.R
R/qmleLevy.R
R/rng.R
R/sampling2grid.R
R/setCarma.R
R/setCogarch.R
R/setHawkes.R
R/setMultiModel.R
R/setPoisson.R
R/setPpr.R
R/sim.euler.R
R/sim.euler.space.discretized.R
R/simCP.R
R/simFunctional.R
R/simulate.R
R/simulateForMapsIntegralAndOperator.R
R/simulateForPpr.R
R/simulateMultiProcess.R
R/spectralcov.R
R/subsampling.R
R/toLatex.R
R/yuima.R
R/yuima.characteristic.R
R/yuima.data.R
R/yuima.functional.R
R/yuima.law.r
R/yuima.model.R
R/yuima.sampling.R
R/zzz.R
data/
data/LogSPX.rda
data/MWK151.rda
inst/
inst/AUTHORS
inst/CITATION
inst/COPYRIGHTS
inst/ybook/
inst/ybook/chapter1.R
inst/ybook/chapter2.R
inst/ybook/chapter3.R
inst/ybook/chapter4.R
inst/ybook/chapter5.R
inst/ybook/chapter6.R
inst/ybook/chapter7.R
man/
man/CPoint.Rd
man/CarmaNoise.Rd
man/DataPpr.Rd
man/Diagnostic.Carma.Rd
man/Diagnostic.Cogarch.Rd
man/IC.Rd
man/Integral.sde.rd
man/Integrand.rd
man/Intensity.PPR.Rd
man/LawMethods.Rd
man/LogSPX.Rd
man/MWK151.Rd
man/adaBayes.Rd
man/asymptotic_term.Rd
man/bns.test.Rd
man/carma.info-class.Rd
man/cce.Rd
man/cogarch.est.incr.rd
man/cogarch.est.rd
man/cogarch.info-class.Rd
man/cogarchNoise.Rd
man/get.counting.data.Rd
man/gmm.rd
man/hyavar.Rd
man/info.Map.Rd
man/info.Ppr.Rd
man/lambdaFromData.Rd
man/lasso.Rd
man/limiting.gamma.Rd
man/llag.Rd
man/llag.test.Rd
man/lseBayes.Rd
man/mllag.Rd
man/mmfrac.Rd
man/model.parameter-class.Rd
man/mpv.Rd
man/noisy.sampling.Rd
man/param.Integral.rd
man/param.Map.Rd
man/phi.test.Rd
man/poisson.random.sampling.Rd
man/qgv.Rd
man/qmle.Rd
man/qmleLevy.Rd
man/rconst.Rd
man/rng.Rd
man/setCarma.Rd
man/setCharacteristic.Rd
man/setCogarch.Rd
man/setData.Rd
man/setFunctional.Rd
man/setHawkes.Rd
man/setIntegral.Rd
man/setLaw.Rd
man/setMap.Rd
man/setModel.Rd
man/setPoisson.Rd
man/setPpr.Rd
man/setSampling.Rd
man/setYuima.Rd
man/simFunctional.Rd
man/simulate.Rd
man/spectralcov.Rd
man/subsampling.Rd
man/toLatex.Rd
man/variable.Integral.rd
man/yuima-class.Rd
man/yuima.CP.qmle-class.Rd
man/yuima.Hawkes.Rd
man/yuima.Integral-class.rd
man/yuima.Map-class.Rd
man/yuima.PPR.qmle-class.Rd
man/yuima.Ppr.Rd
man/yuima.carma-class.Rd
man/yuima.carma.qmle-class.Rd
man/yuima.characteristic-class.Rd
man/yuima.cogarch-class.Rd
man/yuima.data-class.Rd
man/yuima.functional-class.Rd
man/yuima.law-class.rd
man/yuima.model-class.Rd
man/yuima.multimodel.Rd
man/yuima.poisson-class.Rd
man/yuima.sampling-class.Rd
src/
src/IntensityEval.cpp
src/Makevars
src/Makevars.win
src/MpCN.cpp
src/Mt.h
src/PseudoLoglikCOGARCH.c
src/RcppExports.cpp
src/carmafilter.c
src/cce_functions.c
src/euler.c
src/minusquasilogl_W1andW2.cpp
src/pseudoLogLikCogarchIrregularGrid.cpp
src/qmlecpp.cpp
src/rng.c
src/yuima_init.c
yuima.Rproj
Log:
Added: .Rbuildignore
===================================================================
--- .Rbuildignore (rev 0)
+++ .Rbuildignore 2019-09-22 20:36:42 UTC (rev 714)
@@ -0,0 +1,2 @@
+^.*\.Rproj$
+^\.Rproj\.user$
Added: .Rhistory
===================================================================
--- .Rhistory (rev 0)
+++ .Rhistory 2019-09-22 20:36:42 UTC (rev 714)
@@ -0,0 +1,51 @@
+require(Rcpp)
+require(RcppArmadillo)
+debugSource('~/YUIMA/yuima/yuima/R/asymptotic_term_third.R', echo=TRUE)
+require(yuima)
+debugSource('~/YUIMA/yuima/yuima/R/asymptotic_term_third.R', echo=TRUE)
+# to the Black-Scholes economy:
+# dXt^e = Xt^e * dt + e * Xt^e * dWt
+diff.matrix <- "x*e"
+model <- setModel(drift = "x", diffusion = diff.matrix)
+# call option is evaluated by averating
+# max{ (1/T)*int_0^T Xt^e dt, 0}, the first argument is the functional of interest:
+Terminal <- 1
+xinit <- c(1)
+f <- list( c(expression(x/Terminal)), c(expression(0)))
+F <- 0
+division <- 1000
+e <- 4
+yuima <- setYuima(model = model, sampling = setSampling(Terminal=Terminal, n=division))
+yuima <- setFunctional( yuima, xinit=xinit, f=f,F=F,e=e)
+g <- function(x) get_ge(x,epsilon=e,K=1,F0=F0)
+set.seed(123)
+asymp <- asymptotic_term(yuima, block=10, rho,g)
+debug(getf)
+yuima at functional
+source('~/YUIMA/yuima/yuima/R/asymptotic_term_third_function.R', echo=TRUE)
+asymp <- asymptotic_term(yuima, block=10, rho,g)
+source('~/YUIMA/yuima/yuima/R/simFunctional.R', echo=TRUE)
+asymp <- asymptotic_term(yuima, block=10, rho,g)
+X.t0
+plot(X.t0)
+expand.var
+yuima
+yuima at data
+yuima at model
+yuima at model@drift
+yuima at model@diffusion
+e
+yuima at model@xinit
+division
+delta
+dx.drift
+de.drift
+dede.drift
+dx.diffusion
+Y
+plot(Y)
+plot(Y)
+get_e_f0
+mu
+sigma
+Sigma
Added: .Rproj.user/A3842A2/console06/INDEX001
===================================================================
--- .Rproj.user/A3842A2/console06/INDEX001 (rev 0)
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+ "kind" : 6,
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+ "file_last_write" : 1526264951
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+ {
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+ "kind" : 6,
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+ "parent_name" : "",
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+ },
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+ "kind" : 6,
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+ "kind" : 6,
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+ "line" : 84,
+ "name" : "R_init_yuima(DllInfo *)",
+ "parent_name" : "",
+ "usr" : "c:@F at R_init_yuima"
+ }
+ ],
+ "file" : "C:/Users/Emanuele/Documents/YUIMA/yuima/yuima/src/yuima_init.c",
+ "file_last_write" : 1544432752
+ }
+]
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Added: .Rproj.user/A3842A2/pcs/debug-breakpoints.pper
===================================================================
--- .Rproj.user/A3842A2/pcs/debug-breakpoints.pper (rev 0)
+++ .Rproj.user/A3842A2/pcs/debug-breakpoints.pper 2019-09-22 20:36:42 UTC (rev 714)
@@ -0,0 +1,6 @@
+{
+ "debugBreakpointsState" : {
+ "breakpoints" : [
+ ]
+ }
+}
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Added: .Rproj.user/A3842A2/pcs/files-pane.pper
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--- .Rproj.user/A3842A2/pcs/files-pane.pper (rev 0)
+++ .Rproj.user/A3842A2/pcs/files-pane.pper 2019-09-22 20:36:42 UTC (rev 714)
@@ -0,0 +1,9 @@
+{
+ "path" : "~/YUIMA/yuima/yuima/R",
+ "sortOrder" : [
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+ "ascending" : true,
+ "columnIndex" : 2
+ }
+ ]
+}
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Added: .Rproj.user/A3842A2/pcs/source-pane.pper
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+++ .Rproj.user/A3842A2/sources/per/t/2471C01 2019-09-22 20:36:42 UTC (rev 714)
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+++ .Rproj.user/A3842A2/sources/per/t/2471C01-contents 2019-09-22 20:36:42 UTC (rev 714)
@@ -0,0 +1,1430 @@
+
+yuima.warn <- function(x){
+ cat(sprintf("\nYUIMA: %s\n", x))
+}
+
+# in this source we note formulae like latex
+
+
+setGeneric("asymptotic_term",
+ function(yuima,block=100, rho, g, expand.var="e")
+ standardGeneric("asymptotic_term"))
+
+setMethod("asymptotic_term",signature(yuima="yuima"),
+ function(yuima,block=100, rho, g, expand.var="e"){
+
+ if(is.null(yuima at model)) stop("model object is missing!")
+ if(is.null(yuima at sampling)) stop("sampling object is missing!")
+ if(is.null(yuima at functional)) stop("functional object is missing!")
+
+ f <- getf(yuima at functional)
+ F <- getF(yuima at functional)
+
+ ##:: fix bug 07/23
+ #e <- gete(yuima at functional)
+ assign(expand.var, gete(yuima at functional))
+
+ Terminal <- yuima at sampling@Terminal[1]
+ division <- yuima at sampling@n[1]
+ xinit <- getxinit(yuima at functional)
+ state <- yuima at model@state.variable
+ V0 <- yuima at model@drift
+ V <- yuima at model@diffusion
+ r.size <- yuima at model@noise.number
+ d.size <- yuima at model@equation.number
+ k.size <- length(F)
+
+ print("compute X.t0")
+ X.t0 <- Get.X.t0(yuima, expand.var=expand.var)
+ delta <- deltat(X.t0)
+
+ ##:: fix bug 07/23
+ pars <- expand.var #yuima at model@parameter at all[1] #epsilon
+
+ # fix bug 20110628
+ if(k.size==1){
+ G <- function(x){
+ n <- length(x)
+ res <- numeric(0)
+ for(i in 1:n){
+ res <- append(res,g(x[i]))
+ }
+ return(res)
+ }
+ }else{
+ G <- function(x) return(g(x))
+ }
+
+
+ # function to return symbolic derivatives of myfunc by mystate(multi-state)
+
+ Derivation.vector <- function(myfunc,mystate,dim1,dim2){
+
+ tmp <- vector(dim1*dim2,mode="expression")
+
+ for(i in 1:dim1){
+ for(j in 1:dim2){
+ tmp[(i-1)*dim2+j] <- parse(text=deparse(D(myfunc[i],mystate[j])))
+ }
+ }
+
+ return(tmp)
+ }
+
+ # function to return symbolic derivatives of myfunc by mystate(single state)
+
+ Derivation.scalar <- function(myfunc,mystate,dim){
+
+ tmp <- vector(dim,mode="expression")
+
+ for(i in 1:dim){
+ tmp[i] <- parse(text=deparse(D(myfunc[i],mystate)))
+ }
+ return(tmp)
+ }
+
+
+ # function to solve Y_{t} (between (13.9) and (13.10)) using runge kutta method. Y_{t} is GL(d) valued (matrices)
+
+ Get.Y <- function(env){
+
+ ## init
+ dt <- env$delta
+ assign(pars,0) ## epsilon=0
+ Yinit <- as.vector(diag(d.size))
+ Yt <- Yinit
+ Y <- Yinit
+ k <- numeric(d.size*d.size)
+ k1 <- numeric(d.size*d.size)
+ k2 <- numeric(d.size*d.size)
+ k3 <- numeric(d.size*d.size)
+ k4 <- numeric(d.size*d.size)
+ Ystate <- paste("y",1:(d.size*d.size),sep="")
+
+ F <- NULL
+ F.n <- vector(d.size,mode="expression")
+ for(n in 1:d.size){
+ for(i in 1:d.size){
+ F.tmp <- dx.drift[((i-1)*d.size+1):(i*d.size)]
+
+ F.n[i] <- parse(text=paste(paste("(",F.tmp,")","*",
+ Ystate[((n-1)*d.size+1):(n*d.size)],sep=""),
+ collapse="+"))
+ }
+ F <- append(F,F.n)
+ }
+
+ ## runge kutta
+ for(t in 1:(division-1)){
+
+ ## Xt
+ for(i in 1:d.size){
+ assign(state[i],X.t0[t,i]) ## state[i] is x_i, for example.
+ }
+
+ ## k1
+ for(i in 1:(d.size*d.size)){
+ assign(Ystate[i],Yt[i])
+ }
+
+ for(i in 1:(d.size*d.size)){
+ k1[i] <- dt*eval(F[i])
+ }
+
+ ## k2
+ for(i in 1:(d.size*d.size)){
+ assign(Ystate[i],Yt[i]+k1[i]/2)
+ }
+
+ for(i in 1:(d.size*d.size)){
+ k2[i] <- dt*eval(F[i])
+ }
+
+ ## k3
+ for(i in 1:(d.size*d.size)){
+ assign(Ystate[i],Yt[i]+k2[i]/2)
+ }
+
+ for(i in 1:(d.size*d.size)){
+ k3[i] <- dt*eval(F[i])
+ }
+
+ ## k4
+##modified
+ ## Xt+1
+ for(i in 1:d.size){
+ assign(state[i],X.t0[t+1,i])
+ }
+##
+
+ for(i in 1:(d.size*d.size)){
+ assign(Ystate[i],Yt[i]+k3[i])
+ }
+
+ for(i in 1:(d.size*d.size)){
+ k4[i] <- dt*eval(F[i])
+ }
+
+ ## F(Y(t+dt))
+ k <- (k1+k2+k2+k3+k3+k4)/6
+ Yt <- Yt+k
+ Y <- rbind(Y,Yt)
+ }
+
+ ## return matrix : (division+1)*(d.size*d.size)
+ rownames(Y) <- NULL
+ colnames(Y) <- Ystate
+ return(ts(Y,deltat=dt,start=0))
+ }
+
+
+ #l*t
+
+ e_F <- function(X.t0,tmp.F,env){
+
+ d.size <- env$d.size
+ k.size <- env$k.size
+ division <- env$division
+
+ result <- matrix(0,k.size,division)
+
+ assign(pars[1],0)
+
+ de.F <- list()
+
+ for(k in 1:k.size){
+ de.F[[k]] <- parse(text=deparse(D(tmp.F[k],pars[1])))
+ }
+
+ for(t in 1:division){
+ for(d in 1:d.size){
+ assign(state[d],X.t0[t,d])
+ }
+
+ for(k in 1:k.size){
+ result[k,t] <- eval(de.F[[k]])
+ }
+ }
+
+ return(result)
+ }
+
+
+ # function to calculate mu in thesis p5
+ funcmu <- function(e=0,env){
+
+ d.size <- env$d.size
+ k.size <- env$k.size
+ division <- env$division
+ delta <- env$delta
+
+ n1 <- length(get_e_f0)
+ n2 <- sum(get_e_f0 == 0)
+
+ n3 <- length(get_e_F)
+ n4 <- sum(get_e_F == 0)
+
+ n <- (n1 - n2 != 0) * (n3 - n4 != 0)
+
+ if(n == 0){
+ mu1 <- double(k.size)
+ }else{
+ mu1 <- apply(get_e_f0,1,sum) * delta + get_e_F[,division]
+ }
+
+ n5 <- length(get_Y_e_V0)
+ n6 <- sum(get_Y_e_V0 == 0)
+
+ n <- n5 - n6
+
+ if(n == 0){
+ mu2 <- double(k.size)
+ }else{
+ n7 <- length(get_x_F)
+ n8 <- sum(get_x_F == 0)
+
+ n <- n7 - n8
+
+ if(n == 0){
+ mu2_1 <- double(k.size)
+ }else{
+ mu2_1 <- matrix(get_x_F[,,division],k.size,d.size) %*%
+ tmpY[,,d.size] %*% matrix(apply(get_Y_e_V0,1,sum),d.size,1) *
+ delta
+ }
+
+ n9 <- length(get_x_f0)
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/yuima -r 714
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