version 4.2

Author: ac-guidoum

R/MCM.sde.R

@@ -281,7 +281,8 @@ print.MCM.sde <- function(x, digits=NULL, ...)
     if (length(index) > 1) {
        index <- index[1]
        warning("The first element of 'index' will be used")}
-    if (index >  dim(data)[1] | index < 1 ) stop("Subscript out of bounds")
+    if (index >  dim(data)[1] | index < 1 ) 
+	        stop("Subscript out of bounds")
     #if (is.null(x$call$names)) {name <- paste("t",1:dim(data)[1],"*",sep="")}else{
     #name <- sapply(2:length(x$call$names),function(i) x$call$names[[i]])}
     type <- match.arg(type)

tests/MCM_test.R

@@ -1,7 +1,7 @@
 options(prompt="R> ",scipen=16,digits=4,warning=FALSE, message=FALSE)
 library(Sim.DiffProc)
 
-
+RNGkind(kind="L'Ecuyer-CMRG")
 ######
 
 theta = 0.75; x0 = 1
@@ -20,6 +20,8 @@ sde.fun1d <- function(data, i){
      return(c(mean(d),var(d)))
 }
 # Parallel MOnte Carlo for mod1
+mcm.mod1 = MCM.sde(model=mod1,statistic=sde.fun1d,R=5, exact=list(m=E.mod1(1),S=V.mod1(1)))
+mcm.mod1 = MCM.sde(model=mod1,statistic=sde.fun1d,R=5, exact=list(m=E.mod1(1),S=V.mod1(1)),parallel="snow",cl= parallel::makeCluster(getOption("cl.cores", 2)),ncpus=2)
 mcm.mod1 = MCM.sde(model=mod1,statistic=sde.fun1d,R=5, exact=list(m=E.mod1(1),S=V.mod1(1)),parallel="snow",ncpus=2)
 print(mcm.mod1)
 # Parallel MOnte Carlo for mod2
@@ -55,6 +57,8 @@ sde.fun2d <- function(data, i){
   return(c(mean(d$x),mean(d$y),var(d$x),var(d$y),cov(d$x,d$y)))
 }
 ## Parallel Monte-Carlo of 'OUI' at time 10
+mcm.mod2d = MCM.sde(OUI,statistic=sde.fun2d,time=10,R=5,exact=tvalue)
+mcm.mod2d = MCM.sde(OUI,statistic=sde.fun2d,time=10,R=5,exact=tvalue,parallel="snow",cl= parallel::makeCluster(getOption("cl.cores", 2)),ncpus=2)
 mcm.mod2d = MCM.sde(OUI,statistic=sde.fun2d,time=10,R=5,exact=tvalue,parallel="snow",ncpus=2)
 print(mcm.mod2d)
 plot(mcm.mod2d)
@@ -94,6 +98,8 @@ sde.fun3d <- function(data, i){
   return(c(mean(d$x),median(d$x),Mode(d$x),var(d$x),cov(d$x,d$y),cov(d$x,d$z)))
 }
 ## Monte-Carlo at time = 10
+mcm.mod3d = MCM.sde(modtra,statistic=sde.fun3d,R=5)
+mcm.mod3d = MCM.sde(modtra,statistic=sde.fun3d,R=5,parallel="snow",cl= parallel::makeCluster(getOption("cl.cores", 2)),ncpus=2)
 mcm.mod3d = MCM.sde(modtra,statistic=sde.fun3d,R=5,parallel="snow",ncpus=2)
 print(mcm.mod3d)
 plot(mcm.mod3d)
@@ -113,4 +119,5 @@ sde.fun3d <- function(data, i){
 mcm.mod3d = MCM.sde(modtra,statistic=sde.fun3d,R=5,parallel="snow",ncpus=2)
 print(mcm.mod3d)
 plot(mcm.mod3d)
+plot(mcm.mod3d,index=c(1,7))
 

tests/snssde_test.R

@@ -1,4 +1,4 @@
-options(prompt="R> ",scipen=16,digits=4,warning=FALSE, message=FALSE)
+options(prompt="R> ",scipen=16,digits=8,warning=FALSE, message=FALSE)
 library(Sim.DiffProc) 
 
 
@@ -42,7 +42,7 @@ plot(mod1[[1]],type="n",plot.type="single")
 lines(mod1[[1]],col=2,lwd=2)
 points(mod1[[1]],pch=21,col=5,cex=0.5)
 
-s = 0.05547
+s = 0.0554747
 mean(mod1[[1]], at = s)
 moment(mod1[[1]], at = s , center = TRUE , order = 2) ## variance
 Median(mod1[[1]], at = s)
@@ -167,7 +167,7 @@ moment(mod3[[1]], at = s , center= FALSE , order = 4)
 bconfint(mod3[[1]], at =s)
 
 #############################
-
+s= 0.00458
 f <- expression( 2*(1-x) )
 g <- expression( 1 )
 
@@ -176,15 +176,15 @@ plot(mod1,type="n")
 lines(mod1,col=2)
 points(mod1,cex=0.1,pch=19)
 
-mean(mod1)
-moment(mod1, center = TRUE , order = 2) ## variance
-Median(mod1)
-quantile(mod1)
-kurtosis(mod1)
-skewness(mod1)
-cv(mod1)
-min(mod1)
-max(mod1)
+mean(mod1,at = s)
+moment(mod1,at = s, center = TRUE , order = 2) ## variance
+Median(mod1,at = s)
+quantile(mod1,at = s)
+kurtosis(mod1,at = s)
+skewness(mod1,at = s)
+cv(mod1,at = s)
+min(mod1,at = s)
+max(mod1,at = s)
 
 
 ####
@@ -199,15 +199,15 @@ lines(mod2,col=2)
 points(mod2,cex=0.1,pch=19)
 plot2d(mod2)
 
-mean(mod2)
-moment(mod2, center = TRUE , order = 2) ## variance
-Median(mod2)
-quantile(mod2)
-kurtosis(mod2)
-skewness(mod2)
-cv(mod2)
-min(mod2)
-max(mod2)
+mean(mod2,at = s)
+moment(mod2,at = s, center = TRUE , order = 2) ## variance
+Median(mod2,at = s)
+quantile(mod2,at = s)
+kurtosis(mod2,at = s)
+skewness(mod2,at = s)
+cv(mod2,at = s)
+min(mod2,at = s)
+max(mod2,at = s)
 
 ####
 
@@ -221,14 +221,14 @@ lines(mod3,col=2)
 points(mod3,cex=0.1,pch=19)
 plot3D(mod3,display="rgl")
 
-mean(mod3)
-moment(mod3, center = TRUE , order = 2) ## variance
-Median(mod3)
-quantile(mod3)
-kurtosis(mod3)
-skewness(mod3)
-cv(mod3)
-min(mod3)
-max(mod3)
+mean(mod3,at = s)
+moment(mod3,at = s, center = TRUE , order = 2) ## variance
+Median(mod3,at = s)
+quantile(mod3,at = s)
+kurtosis(mod3,at = s)
+skewness(mod3,at = s)
+cv(mod3,at = s)
+min(mod3,at = s)
+max(mod3,at = s)