Hi,
I am trying to calculate the descretionary accruals using the bootstrapping
technique with the R program, but I keep getting an error message.
Previously, after typing in the command on the front sreen, R would return
the output without any problems. I am now using a different
On 10/13/07, Rob Knell [EMAIL PROTECTED] wrote:
I'm trying to do a simulation that involves identifying the minimum
point between two peaks of a (usually) bimodal distribution. I can do
this easily if there are only two peaks:
CnBdens-density(Ys/Xs) #probability density function for ratio of
Josue G. Martinez wrote:
Hello!
I am trying to embed a plot of a curve(say x^2) on a matrix that
I am viewing using the image(matrix) command.
I was wondering if someone could give me some idea
of how to do this.
Hi Jose,
This may be way off what you want, but:
On 12/10/2007, Emmanuel Charpentier [EMAIL PROTECTED] wrote:
Mark Wardle a écrit :
1. Which version of Filemaker? NB: Framemaker is a different program
(desktop publishing), so do be a little precise!
Dunno. The file is named export.fm7 ; one might be tempted to infer
Filemaker 7.
As far as I know you will have to do some work yourself but
if we leverage some of it off the summaryBy function in doBy
its basically just a lapply over the columns.
The first arg to collapse is a formula whose rhs contains the
by variables and whose lhs is ignored. data is our data frame,
The library statement should have been library(doBy). Also note
that collapse assumes that all by variables are factors although
it would only add one statement to collapse to coerce them to
factors if we wanted that.
On 10/13/07, Gabor Grothendieck [EMAIL PROTECTED] wrote:
As far as I know you
Dear R users,
I am using the vars package to calculate the impulse response functions and the
forecast error variance decomposition of a VAR model. Unfortunately I do not
know whether these functions assume unit or one standard deviation shocks. I
tried to look into the code of these
Dear R users,
I am using the vars package to calculate the impulse response functions and the
forecast error variance decomposition of a VAR model. Unfortunately I do not
know whether these functions assume unit or one standard deviation shocks. I
tried to look into the code of these
Dear R users,
I am using the vars package to calculate the impulse response functions and the
forecast error variance decomposition of a VAR model. Unfortunately I do not
know whether these functions assume unit or one standard deviation shocks. I
tried to look into the code of these
I have this code:
list1 - list()
for (i in list.files(pattern=.*c02.*AFDH0.*)){
x - read.table(i,skip=20,fill=TRUE)
list1[[i]] - x
}
Somehow I would like the read.table function to read only values in each
file that are over a certain limit, say 1. Is this the easiest way or is it
better
Dear All,
I am trying to build an error bar plot with ggplot2. However, even if
the code seems to work, the plot is rather odd, with what seems to be
a continuous line linking the different bars.
I attach below the code I used, as well as the data.
Hi Pedro,
That's a bug in the current version of ggplot. I'll try to get a new
version on CRAN soon, but if you let me know what platform you're on,
I can send you a fixed version right away.
Hadley
On 10/13/07, Pedro de Barros [EMAIL PROTECTED] wrote:
Dear All,
I am trying to build an
Hi all,
here others doubts, when load and running the function
void gdot(double *x,double *y,int *n,double *output){
int i;
*output=0;
for (i=0;i*n;i++){
*output+=x[i]*y[i];
}
}
as following
/examplesC$ R CMD SHLIB xby.c
gcc -std=gnu99 -I/usr/share/R/include -I/usr/share/R/include -fpic
You can use 'rle' to find where the direction changes and use that to
determine the peaks:
# create test data
x - seq(-2,7, length=2000)
y - dnorm(x) + dnorm(x,3)
plot(y,type='l')
# find where direction changes from plus to minus
z - rle(diff(y) 0)# find where breaks are
z
Run Length
just store in the list the values you want:
list1 - list()
for (i in list.files(pattern=.*c02.*AFDH0.*)){
x - read.table(i,skip=20,fill=TRUE)
list1[[i]] - subset(x, value 1.0)
}
On 10/13/07, Svempa [EMAIL PROTECTED] wrote:
I have this code:
list1 - list()
for (i in
-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1
The code is C++ and so is compiled
using the C++ compiler, not the C compiler.
This is because the name of the file is .cpp
(and you include iostream.h, but don't seem to make any use of it.)
As a result, the names of the routines are mangled
and so
Let me also comment that you are trying to interface to a function ported
to C++ from the Cephes library, which is in C. You have not explained why
you are trying to interface to the function (is this an exercise, or do
you suspect a problem with digamma()?), but if you just want access to it
as
Dear Rhelp
I am first time user of R and I have the following questions:
1. How I can load my data (it is a matrix 10x1618) with the titles of the
variables in the first row?
2. How I can run vrtest to calculate Variance Ratio Tests for Weak-form Market
Efficiency?
Thanks in advance.
Rutendo Dadiso Kaviya wrote:
Hi,
I am trying to calculate the descretionary accruals using the
bootstrapping technique with the R program, but I keep getting an error
message.
Previously, after typing in the command on the front sreen, R would
return the output without
Yea, sorry, that was a typo when I copied into my emal.
Here it is again
matplot(battingagg$X, battingagg[, c(HR,RBI,X2B, BB,
R, SB)], type=b,lty=4,lwd=2, col=1:4,xlab = Year,
ylab = (1)HRs, (2)RBIs, (3)DOUBLES,(4)BB,(5)Runs,(6) BB,
pty=m,sub = Figure 2. Plot of Selected Offensive
Baseball
On Sat, 2007-10-13 at 22:16 -0500, David Kaplan wrote:
Yea, sorry, that was a typo when I copied into my emal.
Here it is again
matplot(battingagg$X, battingagg[, c(HR,RBI,X2B, BB,
R, SB)], type=b,lty=4,lwd=2, col=1:4,xlab = Year,
ylab = (1)HRs, (2)RBIs, (3)DOUBLES,(4)BB,(5)Runs,(6) BB,
I am pretty sure, it is a unit shock. I think that it says in th
documentation.
On 10/13/07, Martin Ivanov [EMAIL PROTECTED] wrote:
Dear R users,
I am using the vars package to calculate the impulse response functions
and the forecast error variance decomposition of a VAR model.
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