Dear all,
I?m trying to do a graph,
3 rows, 5 columns, with the design:
# 3 4 5 6
# 2
# 7 8 9 10
I had a code for 3 rows, 3 columns, with the design::
# 3 4
# 2
# 7 8
and I tried to modify it, but I had no success :(
I suppose the problem is in the slip.screen code (red part of the code).
I attach my code, can anyone please help me?
Best,
RO
setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
library(ggplot2)
library(reshape)
library(lattice)
# read in what looks like half of the data
bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
quartz(width=10,height=6)
# do the first split, to get the rightmost screen for the legend
split.screen(figs=matrix(c(0,0.8,0,1,0.8,1,0,1),nrow=2,byrow=TRUE))
# now split the first screen to get your six screens for the plots
split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
0.5,1,0.5,1,#primeira linha segunda coluna
0,0.5,0,0.5,#segunda linha primeira coluna
0.5,1,0,0.5),#segunda linha segunda coluna
ncol=4,byrow=TRUE),screen=1)
# this produces seven screens numbered like this:
# 3 4 5 6
# 2
# 7 8 9 10
# select the upper left screen
screen(3)
par(mar=c(0,3.5,3,0))
# now the second set
n250<-bias.alpha1$nsample==250
matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
.6),main="nsample=250",ylab="", cex.main=1)
abline(h = 0, col = "gray60")
mtext(expression(paste("Bias av. for ",alpha[1])),side=2,line=2,
cex.main=1)
screen(4)
par(mar=c(0,0,3,0))
# now the second set
n1000<-bias.alpha1$nsample==1000
matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
.6),main="nsample=1000",ylab="")
abline(h = 0, col = "gray60")
screen(5)
par(mar=c(0,3.5,3,0))
# now the second set
par(mar=c(3,3.5,0,0))
# now the second set
n250<-bias.alpha2$nsample==250
matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
abline(h = 0, col = "gray60")
mtext(expression(paste("Bias av. for ",alpha[2])),side=2,line=2,
cex.main=1.5)
screen(6)
par(mar=c(3,0,0,0))
# now the second set
n1000<-bias.alpha2$nsample==1000
matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1,
.6))
abline(h = 0, col = "gray60")
screen(7)
par(mar=c(0,3.5,3,0))
# now the second set
n250<-SE.alpha1$nsample==250
matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
1.1),main="nsample=250",ylab="", cex.main=1)
abline(h = -1, col = "gray60")
mtext(expression(paste("SE av. for ",alpha[1])),side=2,line=2,
cex.main=1)
mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
screen(8)
par(mar=c(0,0,3,0))
# now the second set
n1000<-SE.alpha1$nsample==1000
matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
1.1),main="nsample=1000",ylab="")
abline(h = -1, col = "gray60")
screen(9)
par(mar=c(3,3.5,0,0))
# now the second set
n250<-SE.alpha2$nsample==250
matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
abline(h = -.5, col = "gray60")
mtext(expression(paste("SE av. for ",alpha[2])),side=2,line=2,
cex.main=1.5)
mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
screen(10)
par(mar=c(3,0,0,0))
# now the second set
n1000<-SE.alpha2$nsample==1000
matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0,
1.1))
abline(h = -.5, col = "gray60")
mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
screen(2)
par(mar=c(0,0,0,0))
# plot an empty plot to get the coordinates
plot(0:1,0:1,type="n",axes=FALSE)
legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
close.screen(all=TRUE)
Best,
RO
Atenciosamente,
Rosa Oliveira
--
____________________________________________________________________________
Rosa Celeste dos Santos Oliveira,
E-mail: rosita21 at gmail.com
Tlm: +351 939355143
Linkedin: https://pt.linkedin.com/in/rosacsoliveira
____________________________________________________________________________
"Many admire, few know"
Hippocrates
Hi Rosa,
Try this:
# do the first split, to get the rightmost screen for the legend
split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
# now split the first screen to get your eight screens (numbered 3 to 10)
for the plots
split.screen(figs=matrix(c(0,0.25,0.5,1,
0.25,0.5,0.5,1,
0.5,0.75,0.5,1,
0.75,1,0.5,1,
0,0.25,0,0.5,
0.25,0.5,0,0.5,
0.5,0.75,0,0.5,
0.75,1,0,0.5),
ncol=4,byrow=TRUE),screen=1)
Jim
On Thu, Sep 17, 2015 at 2:45 AM, Rosa Oliveira <rosita21 at gmail.com>
wrote:
> Dear all,
>
> I?m trying to do a graph,
>
> 3 rows, 5 columns, with the design:
> # 3 4 5 6
> # 2
> # 7 8 9 10
>
> I had a code for 3 rows, 3 columns, with the design::
> # 3 4
> # 2
> # 7 8
> and I tried to modify it, but I had no success :(
>
> I suppose the problem is in the slip.screen code (red part of the code).
>
> I attach my code, can anyone please help me?
>
>
> Best,
> RO
>
>
> setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
>
> library(ggplot2)
> library(reshape)
> library(lattice)
>
>
> # read in what looks like half of the data
>
> bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
> SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
> bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
> SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
>
>
>
> quartz(width=10,height=6)
> # do the first split, to get the rightmost screen for the legend
> split.screen(figs=matrix(c(0,0.8,0,1,0.8,1,0,1),nrow=2,byrow=TRUE))
> # now split the first screen to get your six screens for the plots
>
>
>
> split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
> 0.5,1,0.5,1,#primeira linha segunda coluna
> 0,0.5,0,0.5,#segunda linha primeira coluna
> 0.5,1,0,0.5),#segunda linha segunda coluna
> ncol=4,byrow=TRUE),screen=1)
>
>
> # this produces seven screens numbered like this:
> # 3 4 5 6
> # 2
> # 7 8 9 10
> # select the upper left screen
>
>
>
> screen(3)
> par(mar=c(0,3.5,3,0))
> # now the second set
> n250<-bias.alpha1$nsample==250
> matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
> .6),main="nsample=250",ylab="", cex.main=1)
> abline(h = 0, col = "gray60")
> mtext(expression(paste("Bias av. for ",alpha[1])),side=2,line=2,
> cex.main=1)
>
> screen(4)
> par(mar=c(0,0,3,0))
> # now the second set
> n1000<-bias.alpha1$nsample==1000
> matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
> .6),main="nsample=1000",ylab="")
> abline(h = 0, col = "gray60")
>
>
>
> screen(5)
> par(mar=c(0,3.5,3,0))
> # now the second set
> par(mar=c(3,3.5,0,0))
> # now the second set
> n250<-bias.alpha2$nsample==250
> matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
> type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
> abline(h = 0, col = "gray60")
> mtext(expression(paste("Bias av. for ",alpha[2])),side=2,line=2,
> cex.main=1.5)
>
> screen(6)
> par(mar=c(3,0,0,0))
> # now the second set
> n1000<-bias.alpha2$nsample==1000
> matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6))
> abline(h = 0, col = "gray60")
>
>
>
>
> screen(7)
> par(mar=c(0,3.5,3,0))
> # now the second set
> n250<-SE.alpha1$nsample==250
> matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
> 1.1),main="nsample=250",ylab="", cex.main=1)
> abline(h = -1, col = "gray60")
> mtext(expression(paste("SE av. for ",alpha[1])),side=2,line=2,
cex.main=1)
> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>
>
> screen(8)
> par(mar=c(0,0,3,0))
> # now the second set
> n1000<-SE.alpha1$nsample==1000
> matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
> 1.1),main="nsample=1000",ylab="")
> abline(h = -1, col = "gray60")
>
>
>
>
> screen(9)
> par(mar=c(3,3.5,0,0))
> # now the second set
> n250<-SE.alpha2$nsample==250
> matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
> type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
> abline(h = -.5, col = "gray60")
> mtext(expression(paste("SE av. for ",alpha[2])),side=2,line=2,
> cex.main=1.5)
> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>
>
> screen(10)
> par(mar=c(3,0,0,0))
> # now the second set
> n1000<-SE.alpha2$nsample==1000
> matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1))
> abline(h = -.5, col = "gray60")
> mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
>
>
>
> screen(2)
> par(mar=c(0,0,0,0))
> # plot an empty plot to get the coordinates
> plot(0:1,0:1,type="n",axes=FALSE)
> legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
> lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
>
>
> close.screen(all=TRUE)
>
>
>
>
> Best,
> RO
>
>
> Atenciosamente,
> Rosa Oliveira
>
> --
>
>
____________________________________________________________________________
>
>
> Rosa Celeste dos Santos Oliveira,
>
> E-mail: rosita21 at gmail.com
> Tlm: +351 939355143
> Linkedin: https://pt.linkedin.com/in/rosacsoliveira
>
>
____________________________________________________________________________
> "Many admire, few know"
> Hippocrates
>
> ______________________________________________
> 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]]
Dear Jim,
It works, nonetheless, it doesn't slip the screen correctly :(
Do you have any idea?
I used the code:
#setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
setwd("~/Dropbox/LMER - 3rdproblem/R/latest_version/graphs/data")
library(ggplot2)
library(reshape)
library(lattice)
# read in what looks like half of the data
bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
quartz(width=10,height=6)
# do the first split, to get the rightmost screen for the legend
split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
# now split the first screen to get your eight screens (numbered 3 to 10)
for the plots
split.screen(figs=matrix(c(0,0.25,0.5,1,
0.25,0.5,0.5,1,
0.5,0.75,0.5,1,
0.75,1,0.5,1,
0,0.25,0,0.5,
0.25,0.5,0,0.5,
0.5,0.75,0,0.5,
0.75,1,0,0.5),
ncol=4,byrow=TRUE),screen=1)
#split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
# 0.5,1,0.5,1,#primeira linha segunda coluna
# 0,0.5,0,0.5,#segunda linha primeira coluna
# 0.5,1,0,0.5),#segunda linha segunda coluna
# ncol=4,byrow=TRUE),screen=1)
# this produces seven screens numbered like this:
# 3 4 5 6
# 2
# 7 8 9 10
# select the upper left screen
screen(3)
par(mar=c(0,3.5,3,0))
# now the second set
n250<-bias.alpha1$nsample==250
matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
.6),main="nsample=250",ylab="", cex.main=1)
abline(h = 0, col = "gray60")
mtext(expression(paste("Bias av. for ",alpha[1])),side=2,line=2,
cex.main=1)
screen(4)
par(mar=c(0,0,3,0))
# now the second set
n1000<-bias.alpha1$nsample==1000
matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
.6),main="nsample=1000",ylab="")
abline(h = 0, col = "gray60")
screen(5)
par(mar=c(0,3.5,3,0))
# now the second set
par(mar=c(3,3.5,0,0))
# now the second set
n250<-bias.alpha2$nsample==250
matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
abline(h = 0, col = "gray60")
mtext(expression(paste("Bias av. for ",alpha[2])),side=2,line=2,
cex.main=1.5)
screen(6)
par(mar=c(3,0,0,0))
# now the second set
n1000<-bias.alpha2$nsample==1000
matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1,
.6))
abline(h = 0, col = "gray60")
screen(7)
par(mar=c(0,3.5,3,0))
# now the second set
n250<-SE.alpha1$nsample==250
matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
1.1),main="nsample=250",ylab="", cex.main=1)
abline(h = -1, col = "gray60")
mtext(expression(paste("SE av. for ",alpha[1])),side=2,line=2,
cex.main=1)
mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
screen(8)
par(mar=c(0,0,3,0))
# now the second set
n1000<-SE.alpha1$nsample==1000
matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
1.1),main="nsample=1000",ylab="")
abline(h = -1, col = "gray60")
screen(9)
par(mar=c(3,3.5,0,0))
# now the second set
n250<-SE.alpha2$nsample==250
matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
abline(h = -.5, col = "gray60")
mtext(expression(paste("SE av. for ",alpha[2])),side=2,line=2,
cex.main=1.5)
mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
screen(10)
par(mar=c(3,0,0,0))
# now the second set
n1000<-SE.alpha2$nsample==1000
matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0,
1.1))
abline(h = -.5, col = "gray60")
mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
screen(2)
par(mar=c(0,0,0,0))
# plot an empty plot to get the coordinates
plot(0:1,0:1,type="n",axes=FALSE)
legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
close.screen(all=TRUE)
and I attach the output graph.
Best,
RO
Atenciosamente,
Rosa Oliveira
_________________________________
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N?o imprima, pense na sua responsabilidade e compromisso com o MEIO
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2015-09-17 12:18 GMT+01:00 Jim Lemon <drjimlemon at gmail.com>:
> Hi Rosa,
> Try this:
>
> # do the first split, to get the rightmost screen for the legend
> split.screen(figs=matrix(c(0,0.84,0,1,0.84,1,0,1),nrow=2,byrow=TRUE))
> # now split the first screen to get your eight screens (numbered 3 to 10)
> for the plots
> split.screen(figs=matrix(c(0,0.25,0.5,1,
> 0.25,0.5,0.5,1,
> 0.5,0.75,0.5,1,
> 0.75,1,0.5,1,
> 0,0.25,0,0.5,
> 0.25,0.5,0,0.5,
> 0.5,0.75,0,0.5,
> 0.75,1,0,0.5),
> ncol=4,byrow=TRUE),screen=1)
>
> Jim
>
>
> On Thu, Sep 17, 2015 at 2:45 AM, Rosa Oliveira <rosita21 at
gmail.com> wrote:
>
>> Dear all,
>>
>> I?m trying to do a graph,
>>
>> 3 rows, 5 columns, with the design:
>> # 3 4 5 6
>> # 2
>> # 7 8 9 10
>>
>> I had a code for 3 rows, 3 columns, with the design::
>> # 3 4
>> # 2
>> # 7 8
>> and I tried to modify it, but I had no success :(
>>
>> I suppose the problem is in the slip.screen code (red part of the
code).
>>
>> I attach my code, can anyone please help me?
>>
>>
>> Best,
>> RO
>>
>>
>> setwd("/Users/RO/Dropbox/LMER -
3rdproblem/R/latest_version/graphs/data")
>>
>> library(ggplot2)
>> library(reshape)
>> library(lattice)
>>
>>
>> # read in what looks like half of the data
>>
>> bias.alpha2<-read.csv("graphs_bias_alpha2.csv")
>> SE.alpha2<-read.csv("graphs_SE_alpha2.csv")
>> bias.alpha1<-read.csv("graphs_bias_alpha1.csv")
>> SE.alpha1<-read.csv("graphs_SE_alpha1.csv")
>>
>>
>>
>> quartz(width=10,height=6)
>> # do the first split, to get the rightmost screen for the legend
>> split.screen(figs=matrix(c(0,0.8,0,1,0.8,1,0,1),nrow=2,byrow=TRUE))
>> # now split the first screen to get your six screens for the plots
>>
>>
>>
>> split.screen(figs=matrix(c(0,0.5,0.5,1,#primeira linha primeira coluna
>> 0.5,1,0.5,1,#primeira linha segunda coluna
>> 0,0.5,0,0.5,#segunda linha primeira coluna
>> 0.5,1,0,0.5),#segunda linha segunda coluna
>> ncol=4,byrow=TRUE),screen=1)
>>
>>
>> # this produces seven screens numbered like this:
>> # 3 4 5 6
>> # 2
>> # 7 8 9 10
>> # select the upper left screen
>>
>>
>>
>> screen(3)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> n250<-bias.alpha1$nsample==250
>> matplot(x=bias.alpha1$lambda[n250],y=bias.alpha1[n250,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(-.1,
>> .6),main="nsample=250",ylab="", cex.main=1)
>> abline(h = 0, col = "gray60")
>> mtext(expression(paste("Bias av. for
",alpha[1])),side=2,line=2,
>> cex.main=1)
>>
>> screen(4)
>> par(mar=c(0,0,3,0))
>> # now the second set
>> n1000<-bias.alpha1$nsample==1000
>> matplot(x=bias.alpha1$lambda[n1000],y=bias.alpha1[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(-.1,
>> .6),main="nsample=1000",ylab="")
>> abline(h = 0, col = "gray60")
>>
>>
>>
>> screen(5)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> par(mar=c(3,3.5,0,0))
>> # now the second set
>> n250<-bias.alpha2$nsample==250
>> matplot(x=bias.alpha2$lambda[n250],y=bias.alpha2[n250,3:5],
>> type="l",pch=1:3,col=c(4,2,3),ylim=c(-.1,
.6),ylab="")
>> abline(h = 0, col = "gray60")
>> mtext(expression(paste("Bias av. for
",alpha[2])),side=2,line=2,
>> cex.main=1.5)
>>
>> screen(6)
>> par(mar=c(3,0,0,0))
>> # now the second set
>> n1000<-bias.alpha2$nsample==1000
>> matplot(x=bias.alpha2$lambda[n1000],y=bias.alpha2[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(-.1, .6))
>> abline(h = 0, col = "gray60")
>>
>>
>>
>>
>> screen(7)
>> par(mar=c(0,3.5,3,0))
>> # now the second set
>> n250<-SE.alpha1$nsample==250
>> matplot(x=SE.alpha1$lambda[n250],y=SE.alpha1[n250,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",ylim=c(0,
>> 1.1),main="nsample=250",ylab="", cex.main=1)
>> abline(h = -1, col = "gray60")
>> mtext(expression(paste("SE av. for
",alpha[1])),side=2,line=2,
>> cex.main=1)
>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>
>>
>> screen(8)
>> par(mar=c(0,0,3,0))
>> # now the second set
>> n1000<-SE.alpha1$nsample==1000
>> matplot(x=SE.alpha1$lambda[n1000],y=SE.alpha1[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),xaxt="n",yaxt="n",ylim=c(0,
>> 1.1),main="nsample=1000",ylab="")
>> abline(h = -1, col = "gray60")
>>
>>
>>
>>
>> screen(9)
>> par(mar=c(3,3.5,0,0))
>> # now the second set
>> n250<-SE.alpha2$nsample==250
>> matplot(x=SE.alpha2$lambda[n250],y=SE.alpha2[n250,3:5],
>> type="l",pch=1:3,col=c(4,2,3),ylim=c(0,
1.1),ylab="")
>> abline(h = -.5, col = "gray60")
>> mtext(expression(paste("SE av. for
",alpha[2])),side=2,line=2,
>> cex.main=1.5)
>> mtext(expression(paste(lambda)),side=1,line=2, cex.main=1.5)
>>
>>
>> screen(10)
>> par(mar=c(3,0,0,0))
>> # now the second set
>> n1000<-SE.alpha2$nsample==1000
>> matplot(x=SE.alpha2$lambda[n1000],y=SE.alpha2[n1000,3:5],
>>
type="l",pch=1:3,col=c(4,2,3),yaxt="n",ylim=c(0, 1.1))
>> abline(h = -.5, col = "gray60")
>> mtext(expression(paste(lambda)),side=1,line=2, , cex.main=1.5)
>>
>>
>>
>> screen(2)
>> par(mar=c(0,0,0,0))
>> # plot an empty plot to get the coordinates
>> plot(0:1,0:1,type="n",axes=FALSE)
>> legend(0,0.6,c("OLS", "GLS", "Reg. Cal.",
"0"),bty = "n",
>> lty=1:3,col=c(4,2,3,"gray60"),xpd=TRUE)
>>
>>
>> close.screen(all=TRUE)
>>
>>
>>
>>
>> Best,
>> RO
>>
>>
>> Atenciosamente,
>> Rosa Oliveira
>>
>> --
>>
>>
____________________________________________________________________________
>>
>>
>> Rosa Celeste dos Santos Oliveira,
>>
>> E-mail: rosita21 at gmail.com
>> Tlm: +351 939355143
>> Linkedin: https://pt.linkedin.com/in/rosacsoliveira
>>
>>
____________________________________________________________________________
>> "Many admire, few know"
>> Hippocrates
>>
>> ______________________________________________
>> 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.
>
>
>
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