You used variable names 'Date' and 'Cult' in lm2, but *different*
names 'Cultc52' and 'Dated16' for prediction.
Regards,
Yihui
--
Yihui Xie <[EMAIL PROTECTED]>
Phone: +86-(0)10-82509086 Fax: +86-(0)10-82509086
Mobile: +86-15810805877
Homepage: http://www.yihui.name
School of Statistics, Room 1037,
You seem to have omitted a left quotation mark in (2): %H:%M:%S".
Regards,
Yihui
--
Yihui Xie <[EMAIL PROTECTED]>
Phone: +86-(0)10-82509086 Fax: +86-(0)10-82509086
Mobile: +86-15810805877
Homepage: http://www.yihui.name
School of Statistics, Room 1037, Mingde Main Building,
Renmin University of Ch
Hi all,
I am kind of stuck of using Predict function in R to make prediction
for a model with continuous variable and categorial variables. i have
no problem making the model, the model is e.g.
cabbage.lm2<- lm(VitC ~ HeadWt + Date + Cult)
HeadWt is a continuous variable, Date and Culte are fac
Hi
I have two columns of data with time in form of HH:MM:SS - representing
start time and end time of an activity. I am trying to calculate the time
difference (duration of the activity).
(1) I first tried
> difftime(btime, etime, units = "mins")
This however gave me the error - Error in
as.POSIX
Hi all,
I am kind of stuck of using Predict function in R to make prediction
for a model with continuous variable and categorial variables. i have
no problem making the model, the model is e.g.
cabbage.lm2<- lm(VitC ~ HeadWt + Date + Cult)
HeadWt is a continuous variable, Date and Culte are fac
Frankly, I would do it Duncan's way as that represents it simply as
a linear model but if you insist you could use nls.
nls(dY ~ a0 - a1 * (Y - b1*X) + b0*dX, DF, start = whatever)
On Sat, Oct 4, 2008 at 4:06 PM, Duncan Murdoch <[EMAIL PROTECTED]> wrote:
> On 04/10/2008 3:29 PM, Werner Wernersen
Thanks a lot! It works, however it is less smooth than I had expected.
And I have a further question:
What if I have my own 2-d density function as:
f <- function(x1,x2,parameters)
...
and there is no way how to generate random variates (x1,x2) from f. But I'd
still like to get the contour
Hi Elena,
Currently, there's no way to combine stacking and dodging in a single
graphic. However, you can often use faceting to get a similar effect
to dodging. Could you explain your problem in a little more detail?
Thanks,
Hadley
On Sat, Oct 4, 2008 at 4:22 PM, Elena Schulz <[EMAIL PROTECTE
I'm trying to get the VAR method of the VARS package to work and I get
this weird (probably internal) error:
> usvardata
CBR CDR RGDPGrowthRate
1610416 8.6 -1.98
16105 15.8 8.6 1.62
...
16123 14.4 8.6 3.55
16124 14.39 8.52 2.75
> usvar <- V
Thanks.
Gabor Grothendieck wrote:
Assuming the first row is the comparison row convert
to Date class and calculate:
DF[] <- lapply(DF, as.Date, format = "%Y/%m/%d")
pmin(DF[[2]], DF[1, 2]) - pmax(DF[[1]], DF[1,1])
Please be explicit next time in formulating your queries
as requested in the las
Assuming the first row is the comparison row convert
to Date class and calculate:
DF[] <- lapply(DF, as.Date, format = "%Y/%m/%d")
pmin(DF[[2]], DF[1, 2]) - pmax(DF[[1]], DF[1,1])
Please be explicit next time in formulating your queries
as requested in the last line of every message to r-help.
O
On 10/4/08, Desany, Brian <[EMAIL PROTECTED]> wrote:
> For a non-log-scaled y-axis, I was able to change the appearance of the
> y tick labels in an xyplot by using a custom function for
> yscale.components. However I couldn't get that approach to work for when
> scales=list(y=list(log=TRUE)).
>
Gabor Grothendieck wrote:
Mark did not post his response so I don't know what it
is.
This is Mark's proposal. Sorry, I was speaking about it as if posted to
the list.
# MAKE POSIXct OBJECTS FROM CHARACTER STRINGS
temp1 <- as.POSIXct(strptime("2007-02-02","%Y-%m-%d"))
temp2 <- as.POSIXct(
Peter Dalgaard biostat.ku.dk> writes:
[snip discussion of overrun in seq()]
> > If I don't hear otherwise I will submit this as
> > a bug to r-devel ...
> >
> It IS deliberate We discussed this when R was still in the toddler
> stages.
>
> If you don't allow slight overruns like tha
Dear R users,
I used sm.density function in the sm package and kde2d() in the MASS package
to estimate the bivariate density. Then I calculated the Kullback leibler
divergence meassure between a distribution and the each of the estimated
densities, but the asnwers are different. Is there any diff
Hi ggplot experts,
I need to plot two time series of stacked data: a barchart with bars for
each month. To compare the data of two years I need to combine both time
series with in a single graph via position=doge.
How should I do that?
I tried the following scenario:
I added two layers with t
Werner: what you want done is more easily done using a time series
framework. I think there are examples for doing what you want to in the urca
package or , if not there, then in the associated book of Bernhard Pfaff.
If you send your question to R-Sig-Finance , that may illicit other ideas
besides
On 04/10/2008 3:29 PM, Werner Wernersen wrote:
Hi,
I would like to estimate an error correction model with lm() but I don't find
the correct syntax for that.
The model (leaving out the time indices) looks like:
dY = a0 - a1 * (Y - b1*X) + b0*dX + e
the problem is the term - a1 * (Y - b1*X). H
Hi,
I would like to estimate an error correction model with lm() but I don't find
the correct syntax for that.
The model (leaving out the time indices) looks like:
dY = a0 - a1 * (Y - b1*X) + b0*dX + e
the problem is the term - a1 * (Y - b1*X). How can I restrict a1 to be the same
for both Y a
Thanks Stephen and Gabor. The zoo package is what I was looking for.
On Fri, Oct 3, 2008 at 5:44 PM, Gabor Grothendieck
<[EMAIL PROTECTED]>wrote:
> Check out the zoo package and its three vignettes and
> ?aggregate.zoo in particular.
>
> Also have a look at the article on dates and times in R New
Excel has a solver and Ryacas has limited ability to
do symbolic solving:
> library(Ryacas)
> x <- Sym("x")
> y <- Sym("y")
> Solve(List(x + y == 1, x - y == 1), List(x, y))
[1] "Starting Yacas!"
expression(list(list(x == 1 - y, y == 0)))
On Sat, Oct 4, 2008 at 10:07 AM, Carl Witthoft <[EMAIL PR
On 03/10/2008 7:19 PM, Tomas Lanczos wrote:
Thank You for Your answer, Duncan,
Duncan Murdoch wrote:
On 03/10/2008 4:33 AM, Tomas Lanczos wrote:
hello,
I wish to create some 3d scatter diagrams visualising different
grouped data set by a given field in the database. I tried the
scatterplot3
Please provide complete examples that include test drivers.
Here is main.fun reworked to eliminate the error in the arg
list and also changing the environment of aux.fun:
main.fun <- function(aux.fun, dat) {
x <- 1
environment(aux.fun) <- environment()
aux.fun()
}
aux.fun.one <- function
Rene,
What you have below does not make much sense. You have not provided a
definition for fun.dat() nor have you given an example with which to run
any of your functions.
The issue you raise about passing 'dat variable as a parameter as it can
get pretty large' is not an issue.
Observ
What's wrong with explicitly passing the variables as arguments to the function?
aux.fun.one <- function(dat, x){
median(dat) - x
}
Hadley
On Sat, Oct 4, 2008 at 11:50 AM, René Holst <[EMAIL PROTECTED]> wrote:
> I haven't quite figured out how I can change the environment of a function.
> I ha
I haven't quite figured out how I can change the environment of a function.
I have a main function and want to use different auxillary functions, which I
supply as parameter (or names). What I want to do is something like this:
main.fun=function(aux.fun,dat){
x <- 1
fun.dat()
}
aux.fun.one
Hi,
Is it possible to unload a COM component that is loaded through the
RDCOMClient?
many thanks,
Danny
--
View this message in context:
http://www.nabble.com/Unload-a-COM-component-loaded-through-RDCOMClient-tp19810731p19810731.html
Sent from the R help mailing list archive at Nabble.com.
_
For a non-log-scaled y-axis, I was able to change the appearance of the
y tick labels in an xyplot by using a custom function for
yscale.components. However I couldn't get that approach to work for when
scales=list(y=list(log=TRUE)).
What I'm trying to do is make the y-tick labels show up as some
Hello,
On Thu, Oct 2, 2008 at 3:50 PM, Hanek Martin
<[EMAIL PROTECTED]> wrote:
> Our company has been looking at "SAS enterprise guide 4" (Insightful Miner is
> a similar product from Insightful, I believe) which seems to provide a nice
> graphical way of displaying/managing a process or project
Sorry, mixed up where to place the desired level, it has to be done in
the plot part, as in
d <- kde2d(z1,z2)
contour(d, levels=10^(-(2:9)/2), add=T)
Eik Vettorazzi schrieb:
You may use kde2d from MASS, with estimates a 2d density
d <- kde2d(z1,z2,h=10^(-(2:9)/2))
plot(z1,z2)
contour(d,add=T
You may use kde2d from MASS, with estimates a 2d density
d <- kde2d(z1,z2,h=10^(-(2:9)/2))
plot(z1,z2)
contour(d,add=T)
hth.
biyeshejiqx schrieb:
Hello,everybody,
I used the following codes to generate bivariate normal dependence structure with unit Frechet margins.
Sigma <- matrix(c(
Just thought I'd ask. For those who've never seen TK!Solver, I strongly
recommend taking a look. So far as I can tell, it's the only product of
its type available, retail or open source, for any platform.
What makes TK!Solver so cool is that it adaptively back-solves pretty
much any unknown fr
Hello,everybody,
I used the following codes to generate bivariate normal dependence structure
with unit Frechet margins.
Sigma <- matrix(c(1,.5*sqrt(1),.5*sqrt(1),1),2,2) # generate
y <- mvrnorm(Nsam, c(0,0), Sigma) # random
v <- cbind(pnorm(y[,1],mean = 0, sd = 1), pnorm(y[,2],mean
Erik Iverson wrote:
Depending on the class, you might have another teaching opportunity.
right away after showing your students that (and why) x + 1 - x = 0
Example:
x <- 10^20
x + 1 - x
Uwe Ligges
See R FAQ 7.31 and the document it points to.
Adrian Teo wrote:
I was working on
On Fri, 2008-10-03 at 15:27 -0400, Lo, Ken wrote:
> Hi all,
>
> I am running into a snag using quantile function in stats. Basically, I
> don't understand why the loop below throws the error that it does.
>
> test.data <- rnorm(1000, 0, 1)
>
> for (i in seq(0.1, 0.001, 0.1)){
> te
Hello,
I used the following codes to generate bivariate normal dependence structure
with unit Frechet margins.
Sigma <- matrix(c(1,.5*sqrt(1),.5*sqrt(1),1),2,2) # generate
y <- mvrnorm(Nsam, c(0,0), Sigma) # random
v <- cbind(pnorm(y[,1],mean = 0, sd = 1), pnorm(y[,2],mean = 0, sd =
Ben Bolker wrote:
Lo, Ken roche.com> writes:
Hi all,
I am running into a snag using quantile function in stats. Basically, I
don't understand why the loop below throws the error that it does.
test.data <- rnorm(1000, 0, 1)
for (i in seq(0.1, 0.001, 0.1)){
test <- quantil
Ben Bolker wrote:
Ubuntu.Diego gmail.com> writes:
I'm trying to get some "easy coding" to reproduce the error. In the
meantime I have R code that run for 20 or more hours and suddenly i got
a "segfault 'memory not mapped'" error. I have to clarify that the error
not alway occurs and sometim
38 matches
Mail list logo
