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## Tue Mar 5 18:13:25 2024
## Original file Copyright © 2024 A.C. Guidoum, K. Boukhetala
## This file is part of the R package Sim.DiffProc
## Department of Mathematics and Computer Science,
## Faculty of Sciences and Technology,
## University of Tamanghasset
## and
## Department of Probabilities & Statistics
## Faculty of Mathematics
## University of Science and Technology Houari Boumediene
## BP 32 El-Alia, U.S.T.H.B, Algiers
## Algeria
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
## A copy of the GNU General Public License is available at
## http://www.r-project.org/Licenses/
## Unlimited use and distribution (see LICENCE).
###################################################################################################
#####
##### PredCorr1D
.PredCorr1D <- function(N =1000,M=1,x0=0,t0=0,T=1,Dt,alpha=0.5,mu=0.5,
drift,diffusion,type=c("ito","str"),...)
{
DSx <- Simplify(Deriv(diffusion,"x",cache.exp=FALSE))
if (type=="ito"){A <- function(t,x) eval(drift)}else{
driftstr <- eval(Simplify(substitute(expression(e1 + 0.5 * e2 * de2), list(e1 = drift[[1]], e2 = diffusion[[1]], de2 = Deriv(diffusion,"x",cache.exp=FALSE)[[1]]))))
A <- function(t,x) eval(driftstr)
}
S <- function(t,x) eval(diffusion)
Sx <- function(t,x) eval(DSx)
SS <- function(t,x) A(t,x) - mu * S(t,x) * Sx(t,x)
if (missing(Dt)) {
t <- seq(t0, T, by=Dt)
} else {
t <- c(t0, t0 + cumsum(rep(Dt, N)))
T <- t[N + 1]
}
Dt <- (T - t0)/N
Wu <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wd <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
X = XX <- matrix(x0, N+1, M)
for (i in 1L:N) {
XX[i + 1L,] = XX[i,] + A(t[i],XX[i,])*Dt + S(t[i],XX[i,])*Wu[i,]
X[i + 1L,] <- X[i,] + (alpha*SS(t[i+1],XX[i+1,])+(1-alpha)*SS(t[i],X[i,]))*Dt+(mu*S(t[i+1],XX[i+1,])+(1-mu)*S(t[i],X[i,]))*Wd[i,]
}
name <- "X"
name <- if(M > 1) paste("X",1:M,sep="")
X <- ts(X, start = t0, deltat = Dt, names=name)
return(list(X=X))
}
#####
##### PredCorr2D
.PredCorr2D <- function(N =1000,M=1,x0=0,y0=0,t0=0,T=1,Dt,alpha=0.5,mu=0.5,driftx,
diffx,drifty,diffy,type=c("ito","str"),...)
{
DSx <- Simplify(Deriv(diffx,"x",cache.exp=FALSE))
DSy <- Simplify(Deriv(diffy,"y",cache.exp=FALSE))
if (type=="ito"){
Ax <- function(t,x,y) eval(driftx)
Ay <- function(t,x,y) eval(drifty)
}else{
driftstrx <- eval(Simplify(substitute(expression(e1 + 0.5 * e2 * de2), list(e1 = driftx[[1]], e2 = diffx[[1]], de2 = Deriv(diffx,"x",cache.exp=FALSE)[[1]]))))
driftstry <- eval(Simplify(substitute(expression(e1 + 0.5 * e2 * de2), list(e1 = drifty[[1]], e2 = diffy[[1]], de2 = Deriv(diffy,"y",cache.exp=FALSE)[[1]]))))
Ax <- function(t,x,y) eval(driftstrx)
Ay <- function(t,x,y) eval(driftstry)
}
Sx <- function(t,x,y) eval(diffx)
dSx <- function(t,x,y) eval(DSx)
SSx <- function(t,x,y) Ax(t,x,y) - mu * Sx(t,x,y) * dSx(t,x,y)
Sy <- function(t,x,y) eval(diffy)
dSy <- function(t,x,y) eval(DSy)
SSy <- function(t,x,y) Ay(t,x,y) - mu * Sy(t,x,y) * dSy(t,x,y)
if (missing(Dt)) {
t <- seq(t0, T, by=Dt)
} else {
t <- c(t0, t0 + cumsum(rep(Dt, N)))
T <- t[N + 1]
}
Dt <- (T - t0)/N
Wux <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wdx <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wuy <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wdy <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
X = XX <- matrix(x0, N+1, M)
Y = YY <- matrix(y0, N+1, M)
for (i in 1L:N) {
XX[i + 1L,] = XX[i,] + Ax(t[i],XX[i,],Y[i,])*Dt + Sx(t[i],XX[i,],Y[i,])*Wux[i,]
YY[i + 1L,] = YY[i,] + Ay(t[i],X[i,],YY[i,])*Dt + Sy(t[i],X[i,],YY[i,])*Wuy[i,]
X[i + 1L,] <- X[i,] + (alpha*SSx(t[i+1],XX[i+1,],Y[i,])+(1-alpha)*SSx(t[i],X[i,],Y[i,]))*Dt+(mu*Sx(t[i+1],XX[i+1,],Y[i,])+(1-mu)*Sx(t[i],X[i,],Y[i,]))*Wdx[i,]
Y[i + 1L,] <- Y[i,] + (alpha*SSy(t[i+1],X[i,],YY[i+1,])+(1-alpha)*SSy(t[i],X[i,],Y[i,]))*Dt+(mu*Sy(t[i+1],X[i,],YY[i+1,])+(1-mu)*Sy(t[i],X[i,],Y[i,]))*Wdy[i,]
}
name <- c("X","Y")
name <- if(M > 1) c(paste(name[1],1:M,sep=""),paste(name[2],1:M,sep=""))
X <- ts(X, start = t0, deltat = Dt, names=name[1:M])
Y <- ts(Y, start = t0, deltat = Dt, names=name[(M+1):(2*M)])
return(list(X=X,Y=Y))
}
#####
##### PredCorr3D
.PredCorr3D <- function(N =1000,M=1,x0=0,y0=0,z0=0,t0=0,T=1,Dt,alpha=0.5,mu=0.5,driftx,diffx,drifty,diffy,
driftz,diffz,type=c("ito","str"),...)
{
DSx <- Simplify(Deriv(diffx,"x",cache.exp=FALSE))
DSy <- Simplify(Deriv(diffy,"y",cache.exp=FALSE))
DSz <- Simplify(Deriv(diffz,"z",cache.exp=FALSE))
if (type=="ito"){
Ax <- function(t,x,y,z) eval(driftx)
Ay <- function(t,x,y,z) eval(drifty)
Az <- function(t,x,y,z) eval(driftz)
}else{
driftstrx <- eval(Simplify(substitute(expression(e1 + 0.5 * e2 * de2), list(e1 = driftx[[1]], e2 = diffx[[1]], de2 = Deriv(diffx,"x",cache.exp=FALSE)[[1]]))))
driftstry <- eval(Simplify(substitute(expression(e1 + 0.5 * e2 * de2), list(e1 = drifty[[1]], e2 = diffy[[1]], de2 = Deriv(diffy,"y",cache.exp=FALSE)[[1]]))))
driftstrz <- eval(Simplify(substitute(expression(e1 + 0.5 * e2 * de2), list(e1 = driftz[[1]], e2 = diffz[[1]], de2 = Deriv(diffz,"z",cache.exp=FALSE)[[1]]))))
Ax <- function(t,x,y,z) eval(driftstrx)
Ay <- function(t,x,y,z) eval(driftstry)
Az <- function(t,x,y,z) eval(driftstrz)
}
Sx <- function(t,x,y,z) eval(diffx)
dSx <- function(t,x,y,z) eval(DSx)
SSx <- function(t,x,y,z) Ax(t,x,y,z) - mu * Sx(t,x,y,z) * dSx(t,x,y,z)
Sy <- function(t,x,y,z) eval(diffy)
dSy <- function(t,x,y,z) eval(DSy)
SSy <- function(t,x,y,z) Ay(t,x,y,z) - mu * Sy(t,x,y,z) * dSy(t,x,y,z)
Sz <- function(t,x,y,z) eval(diffz)
dSz <- function(t,x,y,z) eval(DSz)
SSz <- function(t,x,y,z) Az(t,x,y,z) - mu * Sz(t,x,y,z) * dSz(t,x,y,z)
if (missing(Dt)) {
t <- seq(t0, T, by=Dt)
} else {
t <- c(t0, t0 + cumsum(rep(Dt, N)))
T <- t[N + 1]
}
Dt <- (T - t0)/N
Wux <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wdx <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wuy <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wdy <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wuz <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
Wdz <- matrix(rnorm(N * M, 0, sqrt(Dt)), N, M)
X = XX <- matrix(x0, N+1, M)
Y = YY <- matrix(y0, N+1, M)
Z = ZZ <- matrix(z0, N+1, M)
for (i in 1L:N) {
XX[i + 1L,] = XX[i,] + Ax(t[i],XX[i,],Y[i,],Z[i,])*Dt + Sx(t[i],XX[i,],Y[i,],Z[i,])*Wux[i,]
YY[i + 1L,] = YY[i,] + Ay(t[i],X[i,],YY[i,],Z[i,])*Dt + Sy(t[i],X[i,],YY[i,],Z[i,])*Wuy[i,]
ZZ[i + 1L,] = ZZ[i,] + Az(t[i],X[i,],Y[i,],ZZ[i,])*Dt + Sz(t[i],X[i,],Y[i,],ZZ[i,])*Wuz[i,]
X[i + 1L,] <- X[i,] + (alpha*SSx(t[i+1],XX[i+1,],Y[i,],Z[i,])+(1-alpha)*SSx(t[i],X[i,],Y[i,],Z[i,]))*Dt+(mu*Sx(t[i+1],XX[i+1,],Y[i,],Z[i,])+(1-mu)*Sx(t[i],X[i,],Y[i,],Z[i,]))*Wdx[i,]
Y[i + 1L,] <- Y[i,] + (alpha*SSy(t[i+1],X[i,],YY[i+1,],Z[i,])+(1-alpha)*SSy(t[i],X[i,],Y[i,],Z[i,]))*Dt+(mu*Sy(t[i+1],X[i,],YY[i+1,],Z[i,])+(1-mu)*Sy(t[i],X[i,],Y[i,],Z[i,]))*Wdy[i,]
Z[i + 1L,] <- Z[i,] + (alpha*SSz(t[i+1],X[i,],Y[i,],ZZ[i+1,])+(1-alpha)*SSz(t[i],X[i,],Y[i,],Z[i,]))*Dt+(mu*Sz(t[i+1],X[i,],Y[i,],ZZ[i+1,])+(1-mu)*Sz(t[i],X[i,],Y[i,],Z[i,]))*Wdz[i,]
}
name <- c("X","Y","Z")
name <- if(M > 1) c(paste(name[1],1:M,sep=""),paste(name[2],1:M,sep=""),paste(name[3],1:M,sep=""))
X <- ts(X, start = t0, deltat = Dt, names=name[1:M])
Y <- ts(Y, start = t0, deltat = Dt, names=name[(M+1):(2*M)])
Z <- ts(Z, start = t0, deltat = Dt, names=name[(2*M+1):(3*M)])
return(list(X=X,Y=Y,Z=Z))
}
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