The number 332 suggests that this is homework from Peng's online class. Isn't
there there a website for questions regarding these exercises?
I have observed a fair number of similar question on StackOverflow over the
years so you might also search there, since your error is a fairly common one.
Hi
Just to clarify.
Both id and and ncases are numbers. You say you want a vector. In that case
just plain
idcase<-c(idcase,ncases)
shall give you desired vector, provided you initialize idcase before cycle by
idcase <- NA
The code itself is suboptimal but if you have only couple of files it
Hi,
I want this function to read all the 332 files and count the number of
complete rows
in the data. When I run this function, I am getting only the last one.
It should give me id and rowcount for 332 files in one vector.
What am I doing wrong in this code?
complete<-function(id=1:332){
all_
Can anybody provide me with some pointers to some package or code snippets
similar to that of XMLmapper interface of SAS.
XMLmapper reads a xml file and derives by it own "Parent Child relation"
"Child Grandchildren relation" and so on and provide separate csv files for
each hierarchy drill down.
I'm been experimenting with the randomForest R package (v. 4.6-12) and getting
an unexpected difference between rpart and randomForest results that may have
something to do with using x's that are factors.
The same model (see code below) is used to predict a 2-value variable called
"resp" tha
Hi - I'm currently trying to work with a markov chain transition matrix
developed using the markovchain package (it's a 42x42 matrix model). I've
got the matrix up and running smoothly with no problems.
However, I'm trying to run some sensitivity analyses and distribution
analyses on the model, an
Hi Kim,
The only thing that I can think of is that some packages that were
previously loaded automatically may now have to be loaded explicitly. Have
you tried adding:
require(graphics)
to your code?
Jim
On Wed, Jan 27, 2016 at 8:56 PM, Kim Pilegaard wrote:
> I have a function that calls par
On 27/01/2016 4:56 AM, Kim Pilegaard wrote:
I have a function that calls par, it has worked nicely before. Now I get the
following error:
Error in par(mar = c(5.1, 4.1, 5.1, 2.1)) :
there is no .Internal function 'par'
Can anyone give me a hint so solve this problem?
You have a copy of pa
Did you somehow get a copy of the Splus par function into your
R workspace?
Use the conflicts() function to see if you have something masking par.
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Wed, Jan 27, 2016 at 1:56 AM, Kim Pilegaard wrote:
> I have a function that calls par, it has work
On 27.01.2016 10:56, Kim Pilegaard wrote:
I have a function that calls par, it has worked nicely before. Now I get the
following error:
Error in par(mar = c(5.1, 4.1, 5.1, 2.1)) :
there is no .Internal function 'par'
Can anyone give me a hint so solve this problem?
Your R is broken...
I have a function that calls par, it has worked nicely before. Now I get the
following error:
Error in par(mar = c(5.1, 4.1, 5.1, 2.1)) :
there is no .Internal function 'par'
Can anyone give me a hint so solve this problem?
Kim
Kim Pilegaard
Professor
Atmospheric Environment
DTU Environment
Dear R users
I have a question regarding rpart and survey weights. In the introduction
to rpart document it says "Weights are not yet supported, and will be
ignored if present", however they are somehow used as the results are
different with and without weights. Can weights now be used and if yes,
On Wed, 27 Jan 2016 11:51:07 -0500 John Sorkin
wrote:
> I am running normalmixEM:
> mixmdlscaled <- normalmixEM(data$FCWg)
> summary(mixmdlscaled)
> plot(mixmdlscaled,which=2)
>
> If I run the program multiple times, I get widely different results:
>
> > mixmdlscaled <- normalmixEM(data$FCW
You could start by sorting the components, by lambda (size) or by mu (mean)
since, if you don't supply starting values, the order of the components is
random. You could use the following to sort normalmixEM's output:
sort.mixEM <- function (x, decreasing = FALSE, ..., by = "lambda")
{
stopifn
I am running normalmixEM:
mixmdlscaled <- normalmixEM(data$FCWg)
summary(mixmdlscaled)
plot(mixmdlscaled,which=2)
If I run the program multiple times, I get widely different results:
> mixmdlscaled <- normalmixEM(data$FCWg)
number of iterations= 41
> summary(mixmdlscaled)
summary of normalmixE
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