dear Frank,
update() does not update actually.. It just builds a new call which is
evaluated. To speed up the procedure you could try to supply starting
values via argument 'init'. The first values come from the previous
fit, and the last one referring to new coefficients is set to zero (or
Dear R-users,
I have developed the package pyramid, which has been available from CRAN,
but there was little information about how to use it.
Recently I wrote the document for extended usage of pyramid package as
http://minato.sip21c.org/demography/makepyramid-en.html
Any comments are welcome.
On 8/28/19 6:13 AM, Ogbos Okike wrote:
Dear Contributors,
Some of us that use the end product of R could pay for your services
if asked to do so. While all your help is free, I am a little
disturbed that there is no archive or repository where publications
employing R tools are deposited for th
Your first option is always to serially compute results. When the computation
time is long compared to session overhead and data I/O, you can consider
parallel computing. You should first consider laying out your independent
computation work units as a sequence, and then allocate segments of tha
I would suggest that that you search on "parallel computing" at the
Rseek.org site. This brought up what seemed to be many relevant hits
including, of course, the High Performance and parallel Computing Cran task
view.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people
You are right.
On Wed, Aug 28, 2019 at 10:34 AM Jeff Newmiller
wrote:
> Why do you need to do this? It sounds like homework. Using multiple
> columns as lookup keys is the normal way this is handled.
>
> On August 28, 2019 7:10:34 AM PDT, Alex Naverniak
> wrote:
> >Thank you.
> >The problem is
Hi All,
I have a piece of well optimized R code for doing text analysis running
under Linux on an AWS instance. The code first loads a number of packages
and some needed data and the actual analysis is done by a function called,
say, f(string). I would like to parallelize calling this function a
Thank you.
The problem is that I need multiple same size data structures for each item
name. For example: Unique item name -"Table" has several (Lets say 5)
subitems of 3 items in each("Size", "Price", "Qty"); Another item "Chair"
has 4 subitems of the same structure (3 positions in each), etc. Tha
Hello everybody, I come with a question which I do not know how to conduct in
an efficient way. In order to
provide a toy example, consider the dataset "pbc" from the package "survival".
First, I fit the Cox model "Cox0":
library("survival")
set.seed(1)
v <- runif(nrow(pbc), min = 0, max = 2)
Co
Why do you need to do this? It sounds like homework. Using multiple columns as
lookup keys is the normal way this is handled.
On August 28, 2019 7:10:34 AM PDT, Alex Naverniak wrote:
>Thank you.
>The problem is that I need multiple same size data structures for each
>item
>name. For example: Uni
Finally, I did not find the detail of the “R_svmpredict” function that may be a
C program but applying the function named “svmpred” in the svminternals.pdf
document I solved my problem.
Thank you and best regards, Benoit.
De : Sarah Goslee
Envoyé : mercredi 28 août 2019 12:50
À : PELE Benoît (
You could download the package code from CRAN and look yourself at what the
predict function is doing.
Sarah
On Wed, Aug 28, 2019 at 6:35 AM PELE Benoît (Acoss)
wrote:
> Hello everybody,
>
> That is the first time that I am working on a SVM modeling and I would
> like to calculate by myself the
Hello everybody,
That is the first time that I am working on a SVM modeling and I would like to
calculate by myself the result values from the SVM for each line of my database
(named x_appr_svm).
First I tested a linear SVM model using the e1071 package and to calculate the
individual results
Hello,
Just don't include the names of those columns.
Is this what you want?
library(tidyr)
df_initial1 <- data.frame(col1name=c(1,2,3,4,5,6,7),
col2name=c(4,5,6,7,8,9,1), col3name=c(9,8,7,6,5,4,3))
df_initial2 <- data.frame(col1name=c(1,2,3,4,5,6,7),
col2name=c(4,5,6,7,8,9,1))
df_initial3
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