Many thanks Jim. What I,m trying to show with the fhist plot is the empirical distribution of the values of the left plot simulation. You say: However, I don't think that this plot illustrates quite what you think it does. Can you give me a clue to try to illustrate better if it is not showing what I believe it shows a better way to show it? Many thanks in advance. El 7 jun. 2017 12:08, "Jim Lemon" <drjimlemon at gmail.com> escribi?: Hi Pedro, As a one-off, you just shove the coordinates around a bit: par(mar=c(11,0,6,6)) barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray", ylim=c(0,24)) However, I don't think that this plot illustrates quite what you think it does. Jim On Wed, Jun 7, 2017 at 4:01 PM, Pedro p?ramo <percentil101 at gmail.com> wrote:> Please, I'm trying to put the right plot higher and centered on the left > values but I don't achive. > > I would appreciate so much your help > > El 6 jun. 2017 22:37, "Pedro p?ramo" <percentil101 at gmail.com> escribi?: > >> Hi all, >> >> I have this code, but the marginal distribution plot doesn?t appear >> aligned with the left plot. >> >> >> I think could be something about layout or par() mar. >> >> The code was programmed by me time ago. >> >> Can anyone help me to get the marginal distribution on the center (more >> higher centered) >> >> id.txt >> >> Could have this code: >> >> 05/01/2016;9335,200195 >> 06/01/2016;9197,400391 >> 07/01/2016;9059,299805 >> 08/01/2016;8909,200195 >> 11/01/2016;8886,099609 >> 12/01/2016;8915,400391 >> 13/01/2016;8934,5 >> 14/01/2016;8787,700195 >> 15/01/2016;8543,599609 >> 18/01/2016;8469,299805 >> 19/01/2016;8554,900391 >> 20/01/2016;8281,400391 >> 21/01/2016;8444,200195 >> 22/01/2016;8722,900391 >> 25/01/2016;8567,700195 >> 26/01/2016;8692,5 >> 27/01/2016;8741 >> >> >> >> g<-read.table("id.txt", col.names=c("Dateh","LAST"), sep=";", dec=",") >> >> N=5000 >> B=24 >> ghy<-nrow(g) >> r<-as.numeric(as.character(g$LAST[ghy])) >> >> >> nf<-layout(matrix(c(1,1,1,1,2,2),1,6,byrow=TRUE)) >> >> par(mar=c(6,6,6,0.5)) >> >> A<-matrix(1:B,B,N); >> >> >> >> sigma<-0.06; >> >> >> >> mu<-0.00; >> >> >> Z<-r*exp((mu-0.5*((sigma)^2)*A) +sigma*(sqrt(A))*matrix( rnorm(N*B,0,1), >> B, N)) >> >> real1<-g$LAST[1:nrow(g)] >> >> real2<-matrix(NA,nrow(g),N-1) >> >> real<-cbind(real1,real2) >> >> >> >> >> Po<-r*matrix(1,1,N); >> >> >> >> Sim<-rbind(Po,Z) >> Simulation<-rbind(real,Z) >> >> >> >> >> >> >> par(mar=c(10,6,6,6)) >> matplot(Simulation,type="l",ylim=c(0,40000)) >> >> abline(h = 8000, lwd = 2, col = "black") >> >> abline(h = 12000, lwd = 2, col = "black") >> title("Dinamic Montecarlo Simulation 2 years ahead",font=4) >> >> fhist<-hist(Simulation,plot=FALSE) >> par(mar=c(6,0,6,6)) >> barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray") >> grid() >> title("Marginal Distribution",font=4) >> >> >> rect(0, 0, 0, 0) # transparent >> >> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.[[alternative HTML version deleted]]

Please can you send me some orientation? Many thanks in advance. Only if posible one book o similar example to understand why it is not what I try. El 8 jun. 2017 7:50 PM, "Pedro p?ramo" <percentil101 at gmail.com> escribi?:> Many thanks Jim. > > What I,m trying to show with the fhist plot is the empirical distribution > of the values of the left plot simulation. > > You say: > However, I don't think that this plot illustrates quite what you think it > does. > > Can you give me a clue to try to illustrate better if it is not showing > what I believe it shows a better way to show it? > > Many thanks in advance. > > > > > > El 7 jun. 2017 12:08, "Jim Lemon" <drjimlemon at gmail.com> escribi?: > > Hi Pedro, > As a one-off, you just shove the coordinates around a bit: > > par(mar=c(11,0,6,6)) > barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray", > ylim=c(0,24)) > > However, I don't think that this plot illustrates quite what you think it > does. > > Jim > > > On Wed, Jun 7, 2017 at 4:01 PM, Pedro p?ramo <percentil101 at gmail.com> > wrote: > > Please, I'm trying to put the right plot higher and centered on the left > > values but I don't achive. > > > > I would appreciate so much your help > > > > El 6 jun. 2017 22:37, "Pedro p?ramo" <percentil101 at gmail.com> escribi?: > > > >> Hi all, > >> > >> I have this code, but the marginal distribution plot doesn?t appear > >> aligned with the left plot. > >> > >> > >> I think could be something about layout or par() mar. > >> > >> The code was programmed by me time ago. > >> > >> Can anyone help me to get the marginal distribution on the center (more > >> higher centered) > >> > >> id.txt > >> > >> Could have this code: > >> > >> 05/01/2016;9335,200195 > >> 06/01/2016;9197,400391 > >> 07/01/2016;9059,299805 > >> 08/01/2016;8909,200195 > >> 11/01/2016;8886,099609 > >> 12/01/2016;8915,400391 > >> 13/01/2016;8934,5 > >> 14/01/2016;8787,700195 > >> 15/01/2016;8543,599609 > >> 18/01/2016;8469,299805 > >> 19/01/2016;8554,900391 > >> 20/01/2016;8281,400391 > >> 21/01/2016;8444,200195 > >> 22/01/2016;8722,900391 > >> 25/01/2016;8567,700195 > >> 26/01/2016;8692,5 > >> 27/01/2016;8741 > >> > >> > >> > >> g<-read.table("id.txt", col.names=c("Dateh","LAST"), sep=";", dec=",") > >> > >> N=5000 > >> B=24 > >> ghy<-nrow(g) > >> r<-as.numeric(as.character(g$LAST[ghy])) > >> > >> > >> nf<-layout(matrix(c(1,1,1,1,2,2),1,6,byrow=TRUE)) > >> > >> par(mar=c(6,6,6,0.5)) > >> > >> A<-matrix(1:B,B,N); > >> > >> > >> > >> sigma<-0.06; > >> > >> > >> > >> mu<-0.00; > >> > >> > >> Z<-r*exp((mu-0.5*((sigma)^2)*A) +sigma*(sqrt(A))*matrix( > rnorm(N*B,0,1), > >> B, N)) > >> > >> real1<-g$LAST[1:nrow(g)] > >> > >> real2<-matrix(NA,nrow(g),N-1) > >> > >> real<-cbind(real1,real2) > >> > >> > >> > >> > >> Po<-r*matrix(1,1,N); > >> > >> > >> > >> Sim<-rbind(Po,Z) > >> Simulation<-rbind(real,Z) > >> > >> > >> > >> > >> > >> > >> par(mar=c(10,6,6,6)) > >> matplot(Simulation,type="l",ylim=c(0,40000)) > >> > >> abline(h = 8000, lwd = 2, col = "black") > >> > >> abline(h = 12000, lwd = 2, col = "black") > >> title("Dinamic Montecarlo Simulation 2 years ahead",font=4) > >> > >> fhist<-hist(Simulation,plot=FALSE) > >> par(mar=c(6,0,6,6)) > >> barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray") > >> grid() > >> title("Marginal Distribution",font=4) > >> > >> > >> rect(0, 0, 0, 0) # transparent > >> > >> > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posti > ng-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > >[[alternative HTML version deleted]]

Hi Pedro, If you keep that same margins for the second plot: par(mar=c(10,0,6,6)) barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray") it looks reasonably well aligned to me. Because you are plotting the counts of the values in Simulation, the ordinate (vertical axis) of the bar plot is in quite different units from that of the plot on the left side. Jim On Wed, Jun 14, 2017 at 5:33 PM, Pedro p?ramo <percentil101 at gmail.com> wrote:> Please can you send me some orientation? > > Many thanks in advance. > > Only if posible one book o similar example to understand why it is not what > I try. > > El 8 jun. 2017 7:50 PM, "Pedro p?ramo" <percentil101 at gmail.com> escribi?: >> >> Many thanks Jim. >> >> What I,m trying to show with the fhist plot is the empirical distribution >> of the values of the left plot simulation. >> >> You say: >> However, I don't think that this plot illustrates quite what you think it >> does. >> >> Can you give me a clue to try to illustrate better if it is not showing >> what I believe it shows a better way to show it? >> >> Many thanks in advance. >> >> >> >> >> >> El 7 jun. 2017 12:08, "Jim Lemon" <drjimlemon at gmail.com> escribi?: >> >> Hi Pedro, >> As a one-off, you just shove the coordinates around a bit: >> >> par(mar=c(11,0,6,6)) >> barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray", >> ylim=c(0,24)) >> >> However, I don't think that this plot illustrates quite what you think it >> does. >> >> Jim >> >> >> On Wed, Jun 7, 2017 at 4:01 PM, Pedro p?ramo <percentil101 at gmail.com> >> wrote: >> > Please, I'm trying to put the right plot higher and centered on the left >> > values but I don't achive. >> > >> > I would appreciate so much your help >> > >> > El 6 jun. 2017 22:37, "Pedro p?ramo" <percentil101 at gmail.com> escribi?: >> > >> >> Hi all, >> >> >> >> I have this code, but the marginal distribution plot doesn?t appear >> >> aligned with the left plot. >> >> >> >> >> >> I think could be something about layout or par() mar. >> >> >> >> The code was programmed by me time ago. >> >> >> >> Can anyone help me to get the marginal distribution on the center (more >> >> higher centered) >> >> >> >> id.txt >> >> >> >> Could have this code: >> >> >> >> 05/01/2016;9335,200195 >> >> 06/01/2016;9197,400391 >> >> 07/01/2016;9059,299805 >> >> 08/01/2016;8909,200195 >> >> 11/01/2016;8886,099609 >> >> 12/01/2016;8915,400391 >> >> 13/01/2016;8934,5 >> >> 14/01/2016;8787,700195 >> >> 15/01/2016;8543,599609 >> >> 18/01/2016;8469,299805 >> >> 19/01/2016;8554,900391 >> >> 20/01/2016;8281,400391 >> >> 21/01/2016;8444,200195 >> >> 22/01/2016;8722,900391 >> >> 25/01/2016;8567,700195 >> >> 26/01/2016;8692,5 >> >> 27/01/2016;8741 >> >> >> >> >> >> >> >> g<-read.table("id.txt", col.names=c("Dateh","LAST"), sep=";", dec=",") >> >> >> >> N=5000 >> >> B=24 >> >> ghy<-nrow(g) >> >> r<-as.numeric(as.character(g$LAST[ghy])) >> >> >> >> >> >> nf<-layout(matrix(c(1,1,1,1,2,2),1,6,byrow=TRUE)) >> >> >> >> par(mar=c(6,6,6,0.5)) >> >> >> >> A<-matrix(1:B,B,N); >> >> >> >> >> >> >> >> sigma<-0.06; >> >> >> >> >> >> >> >> mu<-0.00; >> >> >> >> >> >> Z<-r*exp((mu-0.5*((sigma)^2)*A) +sigma*(sqrt(A))*matrix( >> >> rnorm(N*B,0,1), >> >> B, N)) >> >> >> >> real1<-g$LAST[1:nrow(g)] >> >> >> >> real2<-matrix(NA,nrow(g),N-1) >> >> >> >> real<-cbind(real1,real2) >> >> >> >> >> >> >> >> >> >> Po<-r*matrix(1,1,N); >> >> >> >> >> >> >> >> Sim<-rbind(Po,Z) >> >> Simulation<-rbind(real,Z) >> >> >> >> >> >> >> >> >> >> >> >> >> >> par(mar=c(10,6,6,6)) >> >> matplot(Simulation,type="l",ylim=c(0,40000)) >> >> >> >> abline(h = 8000, lwd = 2, col = "black") >> >> >> >> abline(h = 12000, lwd = 2, col = "black") >> >> title("Dinamic Montecarlo Simulation 2 years ahead",font=4) >> >> >> >> fhist<-hist(Simulation,plot=FALSE) >> >> par(mar=c(6,0,6,6)) >> >> barplot(fhist$counts,axes=FALSE, space=0,horiz=TRUE,col="lightgray") >> >> grid() >> >> title("Marginal Distribution",font=4) >> >> >> >> >> >> rect(0, 0, 0, 0) # transparent >> >> >> >> >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> >> >