Displaying 20 results from an estimated 300 matches similar to: "Trend graph"
2006 Dec 16
2
how to adjust link function in logistic regression to predict the proportion of correct responses in 2AFC task?
I have would like to use logistic regression to analyze the
percentage of correct responses in a 2 alternative forced
choice task. The question is whether one needs to take into
account the fact expected probabilities for the percentage of
correct responses ranges between 0.5 and 1 in this case and
how to adjust the link function accordingly in R (see details below).
Gabriel
Subjects were asked
2006 Sep 14
2
Patch to fix ArtProvider and ArtProvider sample
These patches better implement ArtProvider and add the demo for it. I
also expanded the bigdemo window a little bit. I really think we should
go larger but I suppose there might be some people at 800x600 still.
Note that creating your own art provider still doesn''t quite work
correctly. I didn''t have time to get into that.
The RubyConstants.i.patch file looks weird. Not
2019 Jan 20
1
NT_STATUS_ACCOUNT_LOCKED_OUT
On Sat, 19 Jan 2019 16:26:21 -0500
Mark Foley via samba <samba at lists.samba.org> wrote:
> On Sun, 20 Jan 2019 08:06:26 +1300 Andrew Bartlett wrote:
> >
> > On Sat, 2019-01-19 at 13:37 -0500, Mark Foley via samba wrote:
> > > I sure could use some help on this. Perhaps this problem is due
> > > to a recent Windows update?
> > >
> > >
2010 Jul 05
1
Linux-Windows problem
Dear All,
I faced the following problem. With the same data.frame the results are
different under Linux and Windows.
Could you help on this topic?
Thanks in advance,
Ildiko
Linux:
> d = read.csv("CRP.csv")
> d$drugCode = as.numeric(d$drug)
> cor(d, use="pairwise.complete.obs")
PATIENT BL.CRP X24HR.CRP X48HR.CRP drug drugCode
PATIENT NA
2018 May 21
2
Bootstrap and average median squared error
Dear R-experts,
I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ?
Here is the reproducible example.
#############################
install.packages( "quantreg" )
library(quantreg)
crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67)
bmi
2007 May 04
0
[1006] trunk/wxruby2/samples/bigdemo/wxArtProvider.rbw: ok method name changed to is_ok
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.1//EN"
"http://www.w3.org/TR/xhtml11/DTD/xhtml11.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head><meta http-equiv="content-type" content="text/html; charset=utf-8" /><style type="text/css"><!--
#msg dl { border: 1px #006 solid; background: #369; padding:
2007 Jan 06
0
[838] trunk/wxruby2/doc/textile/artprovider.txtl: Add methods listing; rubyify examples; distinguish class methods
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.1//EN"
"http://www.w3.org/TR/xhtml11/DTD/xhtml11.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head><meta http-equiv="content-type" content="text/html; charset=utf-8" /><style type="text/css"><!--
#msg dl { border: 1px #006 solid; background: #369; padding:
2018 May 22
2
Bootstrap and average median squared error
I forgot, you should also set.seed() before calling boot() to make the
results reproducible.
Rui Barradas
On 5/22/2018 10:00 AM, Rui Barradas wrote:
> Hello,
>
> If you want to bootstrap a statistic, I suggest you use base package boot.
> You would need the data in a data.frame, see how you could do it.
>
>
> library(boot)
>
> bootMedianSE <- function(data,
2018 May 22
0
Bootstrap and average median squared error
Hello,
If you want to bootstrap a statistic, I suggest you use base package boot.
You would need the data in a data.frame, see how you could do it.
library(boot)
bootMedianSE <- function(data, indices){
d <- data[indices, ]
fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d)
ypred <- predict(fit)
y <- d$crp
median(y - ypred)^2
}
dat <-
2017 Jul 28
3
Superscript and subscrib R for legend x-axis and y-axis and colour different subjects in longitudinal data with different colours
I am trying to make a x-axis and y-axis titles with both a special character and a subscript. I am not being able to do this. I think its just a placing of my parenthesis, but I've tried (seemingly) everything.
Even more, when I try the blog users code it works.
Is it because I?m using longitudinal data?
Even more. Is it possible to colour each one of the 15 lines with a different
2008 Jun 12
1
[7-STABLE] ping -s 4000 with ipsec panic
[FreeBSD 7-STABLE/i386]
Hello,
I've got a 100 % reproductible panic with ipsec when using a
'ping -s 4000'. It works without ipsec
My ipsec setup is very simple, i just use setkey:
/etc/ipsec.conf
flush;
spdflush;
add 192.168.1.21 192.168.1.200 esp 1011 -E rijndael-cbc
"0123456789012345";
add 192.168.1.200 192.168.1.21 esp 1012 -E rijndael-cbc
2018 May 22
0
Bootstrap and average median squared error
On 5/22/2018 2:32 AM, Rui Barradas wrote:
> bootMedianSE <- function(data, indices){
> ???? d <- data[indices, ]
> ???? fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d)
> ???? ypred <- predict(fit)
> ???? y <- d$crp
> ???? median(y - ypred)^2
> }
since the OP is looking for the "median squared error", shouldn't the
final line of the
2018 May 22
1
Bootstrap and average median squared error
Hello,
Right!
I copied from the OP's question without thinking about it.
Corrected would be
bootMedianSE <- function(data, indices){
d <- data[indices, ]
fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d)
ypred <- predict(fit)
y <- d$crp
median((y - ypred)^2)
}
Sorry,
rui Barradas
On 5/22/2018 11:32 AM, Daniel Nordlund wrote:
> On 5/22/2018
2009 Nov 05
2
faxes received on mISDN
Hi,
My initial setup for receiving faxes worked as follows:
fax call arrives on ISDN BRI connected to a BOSCH PBX, signal sent to ALCATEL PBX via PRI QSIG then finally sent to ASTERISK via PRI EUROISDN. The Asterisk server then forwarded the call to a iaxmodem and HylaFax received the data. All worked fine.
Now I got rid of both BOSCH and ALCATEL in the "fax path" and it's as
2009 Nov 08
2
linear trend line and a quadratic trend line.
Dear list users
How is it possible to visualise both a linear trend line and a quadratic trend line on a plot
of two variables?
Here my almost working exsample.
data(Duncan)
attach(Duncan)
plot(prestige ~ income)
abline(lm(prestige ~ income), col=2, lwd=2)
Now I would like to add yet another trend line, but this time a quadratic one. So I have two
trend lines. One linear trend line
2017 Jul 31
2
Superscript and subscrib R for legend x-axis and y-axis and colour different subjects in longitudinal data with different colours
> Hi Rosa
> something like
> plot(1,1, sub=expression(lambda^"2"))
> So with your example, do you want something like
> plot(c(1:5), CRP7raw[1,], type = "n", xlim=c(1,5), ylim=c(-10,5) ,
> xlab="Day in ICU",
> ylab="CRP (mg/dL)",
> sub = mtext(expression(lambda^2)))
OOps! Either plot( ..., sub = *)
or
2017 Jul 31
4
Superscript and subscrib R for legend x-axis and y-axis and colour different subjects in longitudinal data with different colours
>>>>> PIKAL Petr <petr.pikal at precheza.cz>
>>>>> on Mon, 31 Jul 2017 09:11:18 +0000 writes:
> Hi Martin see in line
>> -----Original Message----- From: Martin Maechler
>> [mailto:maechler at stat.math.ethz.ch] Sent: Monday, July
>> 31, 2017 10:52 AM To: PIKAL Petr <petr.pikal at precheza.cz>
>> Cc:
2010 Jan 21
2
3d trend line
I have a 3d scatter plot and I need to add a trend line. I can add a
regression plane, but I need a line, not a plane.
Thanks.
--
View this message in context: http://n4.nabble.com/3d-trend-line-tp1053686p1053686.html
Sent from the R help mailing list archive at Nabble.com.
2011 Oct 31
1
Significance of trend
Hi everyone,
I'm trying to determine the significance of a trendline. From my internet
search months ago, I came across the following post. I modified tim and
dat for simiplicity.
tim <- 1:10
dat <- c(0.17, 1.09 ,0.11, 0.82, 0.23, 0.38 ,2.47 ,0.41 ,0.75, 1.44)
fstat <- summary(lm(dat~tim))$fstatistic
p.val <-
2011 Mar 30
1
VECM with UNRESTRICTED TREND
Dear All,
My question is:
how can I estimate VECM system with "unrestricted trend" (aka "case 5")
option as a deterministic term?
As far as I know, ca.jo in urca package allows for "restricted trend"
only [vecm
<- ca.jo(data, type = "trace"/"eigen", ecdet = "trend", K = n, spec =
"transitory"/"longrun")].