Here is a demo you may like to consider. (I can see what you are trying
to do with your loops, but I prefer to do it this way.)
On 32 bit Windows, (which I am forced to use), your seed is not a valid
integer, so I have changed it to something which is.
> set.seed(7658943)
>
> fph <- 0.4
> Sigh
Why do you keep posting something to which you have already received an
answer?
https://stat.ethz.ch/pipermail/r-help/2008-April/158662.html
answered in
https://stat.ethz.ch/pipermail/r-help/2008-April/158664.html
and repeated at
https://stat.ethz.ch/pipermail/r-help/2008-April/158787.html
and
h
Hi,
I have a regression model, where the explanatory variables are factors,
and I want to include interaction terms, but some combinations occur in
the data very infrequently.
Hence, I'm using hclust and cutree to hierarchically cluster the levels,
and get new combined levels to regress on.
I
hi,
i wrote in R
VSS(data,number of factors to extract ex1 )OK
dofchisq prob sqresid fit cfit cresidual
1 54 107.8943 1.860272e-05 18.51662 0.3444595 0.3444595 18.51662
VSS(data,number of factors to extract 2 )OK
dof chisq prob sqresid fit
I am caught in a mental trap. Why isn't the between groups variance estimated
(0.0038) to be around the value with which I generated the data (0.0002)?
Thanks Toby
set.seed(76589437887)
fph = 0.4
Sigh = sqrt(0.0002)
Sigi = sqrt(0.04)
ci = 1
fpi = matrix(,7200,3)
for (i in 1:90) {
fph =
Prof Brian Ripley wrote:
> This is not an LAPACK error, but an R function chol2inv complaining that
> it is being misused.
>
> The problem is that you have a vastly overparametrized model (using
> recover())
>
> Browse[1]> dim(X)
> [1] 20 143
>
> and ols() does not detect that, whereas lm() w
You must add a check for the NAs:
> a[(a$V1 > 1) & (!is.na(a$V1)),]
V1V2V3 V4 V5
7 100 -2.343761 -132.6063 101.7575 1.187004
On Sat, Apr 5, 2008 at 8:05 PM, Georg Ehret <[EMAIL PROTECTED]> wrote:
> Dear R community,
>I am using a dataframe with lots of NAs and
Dear R community,
I am using a dataframe with lots of NAs and wish to create subsets from
that dataframe. In the example below I intend to create a subset with all
entries with V1>1. To my surprise the result also contains all entries with
V1=NA. I would wish to learn more why this is or what I
Dear All,
I would be very appreciative of your help with the following
1). I am running multivariate multiple regression through the manova()
function (kindly suggested by Professor Venables) and getting two different
answers for test=c("Wilks","Roy","Pillai") and tests=c("Wilks","Roy
Hi again,
Is this approach correct, or should I rather use only one type of
factors (combined)? I must admit I am a bit confused by the different
options to store and manipulate data in R. As I understand,
data.frames are the preferred format, but I can't see how to frame
this example data
Dear Katheryn:
I'm confused by your claim that, "Even though I used the true
parameter values as initial values, the results are not very good."
When I ran it, 'optim' quit with $value = -35835, substantially
less than fr2(theta0) = -0.3.
Could you please review your quest
The difference may be due to different handling of missing values.
If you do cor(x,y) "by hand" in excel, you use all available information
of x and y to calculate sd(x) and sd(y) seperately. But cov(x,y) in
excel will use only complete pairs of (x,y), which is likely not the
same set. So your
kate uiuc.edu> writes:
[snip]
>
> When I read this txt file into R and attach this data, I found the output of y
is as the follows
> [1] 8 5 3 + -1 +
> Levels: -1 + 3 5 8
>
> Could I get rid of Levels in the output? Because I need to use the observed y
and x run regression first and t
Hi,
I have (x, y) data as the follows (saved in the txt file):
x y
1 8
2 5
3 3
4 +
5 -1
6 +
When I read this txt file into R and attach this data, I found the output of y
is as the follows
[1] 8 5 3 + -1 +
Levels: -1 + 3 5 8
Could I get rid of Levels in the output? Because I need
> I used the function cor to calculate the pearson correlation coefficient
> between variables. However, the resulting values do not correspond to the
> outcome of my excel-calculations, for which I used the formula
> Cor(x,y)=Cov(x,y)/(SD(x)*SD(y)) So my question is: How does the function
> "cor"
On Sat, 5 Apr 2008, Prof Brian Ripley wrote:
> Why are you asking here if you should submit a bug report on your compiler?
I was asking so that I'd get exactly this answer back!
More seriously, I thought there was a chance that the problem was
specific to the particular compilation, but I know
On Sat, 5 Apr 2008, Larry Snyder wrote:
> On Sat, 5 Apr 2008, Prof Brian Ripley wrote:
>
>> Why are you asking here if you should submit a bug report on your compiler?
>
> I was asking so that I'd get exactly this answer back!
>
> More seriously, I thought there was a chance that the problem was s
Dear All,
I would be very appreciative of your help with the following
1). I am running multivariate multiple regression through the manova()
function (kindly suggested by Professor Venables) and getting two different
answers for test=c("Wilks","Roy","Pillai") and tests=c("Wilks","R
Hello,
I used the function cor to calculate the pearson correlation coefficient
between variables. However, the resulting values do not correspond to the
outcome of my excel-calculations, for which I used the formula
Cor(x,y)=Cov(x,y)/(SD(x)*SD(y))
So my question is: How does the function "cor
Why are you asking here if you should submit a bug report on your
compiler? This is not a bug in R, but in your compilation enviroment.
If you update your compiler you may well need to reinstall R -- you did
not mention that you did so.
BTW, R is not setting '-mcpu=i686 -pipe', but your Linux
Hello,
The labels that I add to plots using the "identify" function disappear
when I export or copy the graphics as metafiles.
Copying as bitmap keeps the labels in the plot but the quality of these
graphics is much lower than that of the metafiles.
What may cause this problem? And how could it
For information, the R-devel version of R now has an experimental function
setTimerLimit() to set time limit(s) (elapsed and/or CPU) for each
top-level function. It will be a while before (or even if) it is
released, but it may prove useful to those with an immediate need.
On Wed, 2 Apr 2008
>From http://bugs.r-project.org/cgi-bin/R:
If you are not sure whether you have observed a bug or not, it is a good
idea to ask on the mailing list R-Help by sending an e-mail to
[EMAIL PROTECTED] rather than submitting a bug report.
I'm wondering whether to submit a bug report on this:
> How can I read and plot an ArcGIS raster file into R ?
Hi Juliane,
I think what you are looking for is something like a function in the
"adehabitat" package called "import.asc". First you need to convert your
raster images in ArcGIS to ascii files. You have to use the conversion
toolbox -->
Armin Goralczyk wrote:
> Hi list
> Maybe someone can help with the following problem (thanks in advance):
>
> In a function I have a plot and want to add symbols/text only when
> indicated by a logical vector (which was generated by the function
> before, not manually like in the following example
Armin Goralczyk gmail.com> writes:
> In a function I have a plot and want to add symbols/text only when
> indicated by a logical vector (which was generated by the function
> before, not manually like in the following example):
>
> plot(1:10, 1:10)
> lv <- c(T,T,T,F,F,F,T,T,T,F)
> text(1:10, 1:10
Liviu Andronic gmail.com> writes:
>
> Hello,
>
> On Fri, Apr 4, 2008 at 8:09 PM, Martin Rittner thegeologician.net>
wrote:
> > I don't know too much about R myself, but a little about ArcGIS:
Come on, please do use a little time to search! An RSiteSearch("Arc raster")
gets you lots of hits o
Hi list
Maybe someone can help with the following problem (thanks in advance):
In a function I have a plot and want to add symbols/text only when
indicated by a logical vector (which was generated by the function
before, not manually like in the following example):
plot(1:10, 1:10)
lv <- c(T,T,T,
Dear R users,
I used to "OPTIM" to minimize the obj. function below. Even though I used
the true parameter values as initial values, the results are not very good.
How could I improve my results? Any suggestion will be greatly appreciated.
Regards,
Kathryn Lord
#
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