ARMIDALE NSW 2351
-- Original Message --
From: "Phat Chau"
To: "r-help@R-project.org" ; "sor...@math.aau.dk"
Sent: Sunday, 12 Jul, 2020 At 11:52 PM
Subject: Re: [R] Multi-level (nested) correlation structures via
geepack package
He
quot;r-help@R-project.org" ; "sor...@math.aau.dk"
Sent: Sunday, 12 Jul, 2020 At 11:52 PM
Subject: Re: [R] Multi-level (nested) correlation structures via
geepack package
Hello,
I have a multi-level, cohort dataset with three levels: repeat measures
of a response (level 1), that ar
You may get lucky, but generally such package-specific questions don't get
responses here. There are about 2 packages after all. You might do
better posting on the r-sig-mixed-models list or by asking the package
maintainer (?maintainer) whether there is some sort of support list for the
packag
Hello,
I have a multi-level, cohort dataset with three levels: repeat measures of a
response (level 1), that are collected from individual participants (level 2)
who are students within a school (level 3). I would like to do a generalized
estimating equation (GEE) analysis of this clustered dat
You might want to start by re-expressing the "amounts"
variables to
total amount * (relative fish 1, relative fish 2, invertebrates)
and then using the Isometric Log-ratio transformation to
convert the compositional part to orthonormal coordinates.
https://stats.stackexchange.com/questions/259208
-project.org
Subject: Re: [R] Multi response GAM
https://cran.r-project.org/web/views/Multivariate.html
https://cran.r-project.org/web/views/Environmetrics.html
https://cran.r-project.org/web/views/TimeSeries.html
Also search on "multiresponse GAM" or similar at rseek.org<http://rsee
--
Message: 5
Date: Fri, 17 Apr 2020 22:45:33 +
From: Tristan Kosciuch
To: "r-help@R-project.org"
Subject: [R] Multi response GAM
Message-ID:
Content-Type: text/plain; charset="utf-8"
Hello,
I am modelling the diet of Nile perch through time. I have
https://cran.r-project.org/web/views/Multivariate.html
https://cran.r-project.org/web/views/Environmetrics.html
https://cran.r-project.org/web/views/TimeSeries.html
Also search on "multiresponse GAM" or similar at rseek.org. This brought up
what looked to me like useful hits.
And of course, don't
It might be possible via the VGAM package:
https://cran.r-project.org/package=VGAM
But I've never used this package, so not sure.
It may also be possible to use a single response, by including
additional explanatory terms.
This is what I would do, if I could...
Noting that some GAM implementatio
Hello,
I am modelling the diet of Nile perch through time. I have 3 diet classes as
my response variables; fish 1, fish 2, and invertebrates.
The response variables are correlated, declines in invert consumption ~
increase in fish consumption. Any advice on how to handle this would be
appreciated
Hi all, this is my first post so sorry if there's something wrong.
I'm doing a project for university, and I should have to do the rolling windows
forecasting for 2 or more step ahead.
Does anyone know a code (or a cycle "for") to overpass the problem of
"n.ahead=1"? Thanks a lot for who will ans
You forgot to reply-all ... I don't do private consulting, so please keep
the conversation on the mailing list.
Here are some ideas for extending your example. However, whether you WANT
to or not, you really need to learn to manipulate your data BEFORE you
give it to ggplot.
a) missing ggplot2 library
b) cannot word wrap in the middle of a string in R without introducing
newlines
c) aes is not recommended for working with string variables as names...
use aes_string
d) Because aes_string will parse the string, you need to add the backticks
e) paste0() is a shorter v
Hi Philip,
This may work:
library(dplyr)
`RefDate` <- as.Date(c("2010-11-1","2010-12-01","2011-01-01"))
`Number of vegetables` <- c(14,23,45)
`Number of people` <- c(20,30,40)
MyData <- data.frame(RefDate,`Number_of_vegetables`,
`Number_of_people`,check.names=FALSE)
MyVars <- c("Number of vegetab
I am having trouble working with column names in a data frame. My
column names are multi-word text strings and I like it that way. I
want to loop through the columns, plotting graphs for each one, and I
want to use the column names in the chart labels and in the file names
when I save the c
Arun,
I would suggest either getting enrolled in a multivariate statistics class and
the pre-requisites for this or going back to your boss and asking him or her to
hire a MS-level statistician since this is clearly beyond your current state of
knowledge.
Don't expect R-help to be a free cons
Hi All,
I have been given three raw data csv files related to an advertising
campaign. Impressions, clicks and conversion. They asked me to suggest
optimisation suggestions using uni variable and multi variable analysis.
The clicks or conversions are spread across various parameters like device,
c
Hi Vadim,
I would be happy to explore helping you out with this. I am quite active
in development for GPU use in R. You can see my work on my github (
https://github.com/cdeterman) and the group I created for additional
packages in development (https://github.com/gpuRcore). I believe it would
b
¡Hola!
This is to announce that [kmcuda](https://github.com/src-d/kmcuda) has
obtained native R bindings and ask for the help with CRAN packaging.
kmcuda is my child: an efficient GPGPU (CUDA) library to do K-means
and K-nn on as much data as fits into memory. It supports running on
multiple GPUs
Dear Janina
On 18/11/2016 12:04, Janina Steinert wrote:
Hi!
I am running a multi-level meta-regression in R using the metafor package.
I have specified a univariate multi-level meta-regression as follows:
Test_MR <- rma.mv(yi = effectsize_estimates, V = effsize_sd2, data = Test,
Hi!
I am running a multi-level meta-regression in R using the metafor package.
I have specified a univariate multi-level meta-regression as follows:
Test_MR <- rma.mv(yi = effectsize_estimates, V = effsize_sd2, data = Test,
mods = ~ x, random = list(~ 1 | coeff, ~ 1 | study))
C
Read Ella
Comments in-line below
On 14/08/2015 00:36, mcknight e. (em8g14) wrote:
Hello,
I am working on ecological data covering a meta-analysis on invasive species
traits.
I am not very skilled in R and would love if someone could assist me in my
production of multi-line forest plots.
Hello,
I am working on ecological data covering a meta-analysis on invasive species
traits.
I am not very skilled in R and would love if someone could assist me in my
production of multi-line forest plots.
The data I have is: random effects mixed model and is further divided into
subsets, I
On 15/07/2015 2:33 PM, Vyshnnavi Parthasarathy wrote:
> Hello,
> I am using a 8 core processor system. Is there a way to run different R
> scripts on different cores instead of all scripts running on the same core?
> If I open a new RStudio session for each script, can I somehow assign each
> Rstud
Hello,
I am using a 8 core processor system. Is there a way to run different R
scripts on different cores instead of all scripts running on the same core?
If I open a new RStudio session for each script, can I somehow assign each
Rstudio session to a particular core processor so as to make the proc
Hi Yuan,
You can start reading the following site:
http://cran.r-project.org/web/views/HighPerformanceComputing.html
Regards,
Pascal
On Wed, Sep 10, 2014 at 2:56 PM, Yuan Luo wrote:
> Hi,
> I am merging large data frames and it would be great if I can run merge in
> multi-threading/parallel mod
Hi,
I am merging large data frames and it would be great if I can run merge in
multi-threading/parallel mode. Can someone point me to the right way to do
it?
Best,
Yuan
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R-help@r-project.org mailing list
h
It's easier for folks to help you if you make your data available by
reproducible code. You can do this using the dput() function. So, for
example, you could share your hessianList with us using
dput(hessianList)
and then including this code in your post
hessianList <- list(structure(c(0.00
Hi,
May be this helps:
set.seed(42)
list1 <- lapply(1:3, function(i) matrix(rnorm(4),2,2))
g <- c(1,2,3)
fun1 <- function(g,hessianList){
mat1 <- vector(mode="list",length=length(g))
for(i in seq_along(g)){
mat1[[i]] <- g[i]*hessianList[[i]]
}
Reduce(`+`,mat1)
[[1]]
[,1] [,2]
[1,] 0.003632559 0.2190629
[2,] -2.090772847 0.2190629
[[2]]
[,1] [,2]
[1,] 0.004278991 0.04337005
[2,] 0.190723602 0.04337005
[[3]]
[,1] [,2]
[1,] 0.01237827 -0.01544811
[2,] 0.06452200 -0.01544811
g<-c(1,2,3)
function(g,
I have a data set with 20K variables. I want to apply Boruta feature
selection but I get cannot allocate vector of size error. Hence, I decided
to use bigmemory like below script but it seems that Boruta does not accept
a pointer. How can I apply feature selection to 20K variables?
df <- data with
Hi,
You can upload the dataset using:
library(XLConnect)
wb<-loadWorkbook("excel_data.xlsx")
dat1<- readWorksheet(wb,sheet="excel data",region="A1:DA101") #region can be
specified to read a subset of the dataset. Here, I read the full #dataset.
dim(dat1)
#[1] 100 105
str(dat1)
#'data.frame':
Hi,
May be this helps:
dat1<- read.table(text="
ID county date company
1 x 1 comp1
2 y 1 comp3
3 y 2 comp1
4 y 3 comp1
5 x 2 comp2
",sep="",header=TRUE,stringsAsFactors=FALSE)
dat2<- dat1
dat1$answer<-unsplit(lap
Hi,
Thanks in advance.
I am using R-3.0.1 on Windows XP.
May I request you to assist me for the following please.
I have a data set where each instance has two or more levels. As for example,
level 1 (binary): 0, 1; level 2 (binary): 0, 1 and so on. These levels are
target variables. The
Hello all,
Running the "msprep" function of the "mstate " package
R showsmethe following error:
Error in hlpsrt[, 1] - hlpsrt[, 2] :
non-numeric argument to binary operator
what "hlpsrt" is?
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R-help@r-pr
Dear list,
I am trying to do an automated model selection of a glmm (function glmer;
package: lme4) containing a large number of predictors. As far as i
understand, glmulti is able to devide the process into chuncks and proceed
by parallel processing on on multiple cores. Unfortunately this does n
On 05.04.2013 14:15, lejeczek wrote:
hi everybody
the subject may seem a bit over the top but,
I wonder if there is way in R to separate/segregate users
into different access levels/categories
simply, user A cannot perform certain tasks, cannot use
certain libraries or their certainfunctions?
hi everybody
the subject may seem a bit over the top but,
I wonder if there is way in R to separate/segregate users
into different access levels/categories
simply, user A cannot perform certain tasks, cannot use
certain libraries or their certainfunctions?
possible now? in the futuremaybe?
reg
Many thanks
At 2013-03-14 00:23:43,"Richard M. Heiberger" wrote:
Meng,
What seems to be going on is that the covariates are handled very differently
in TukeyHSD and in glht.
Please see the interaction_average and covariate_average arguments to glht.
I ran your example twice, firs
Meng,
What seems to be going on is that the covariates are handled very
differently in TukeyHSD and in glht.
Please see the interaction_average and covariate_average arguments to glht.
I ran your example twice, first as you did, with the covariates after the
factor.
x2 is not significant if the
Hi all:
I have a question about multi-comparison.
The data is in the attachment.
My purpose:
Compare the predicted means of the 3 methods(a,b,c) pairwisely.
I have 3 ideas:
#idea1
result_aov<-aov(y~ method + x1 + x2)
TukeyHSD(result_aov)
difflwr upr p adj
b-a 0.845
Forgot to cc the help list.
On 18-12-2012, at 19:40, Lu, James T wrote:
> I am attempting to use optim to solve a neural network problem. I would like
> to optimize coefficients that are currently stored in a matrix
>
> Y=270 x 1
> X= 27- x 14
> b1= 10x14
> b2= 11x1
> V= 10 x 14 set of prior
I am attempting to use optim to solve a neural network problem. I would like
to optimize coefficients that are currently stored in a matrix
Y=270 x 1
X= 27- x 14
b1= 10x14
b2= 11x1
V= 10 x 14 set of prior variances.
I have the following function:
posterior.mode1=function(y,X,b_0,b2,V) {
log
A perhaps more "elegant" way to do it would be to use the ?layout
function rather than the ancient mfrow() to create space for both
titles and graphs. You could then e.g. "draw" your titles in the space
you created for titles.
-- Bert
On Wed, Oct 24, 2012 at 5:33 AM, Jean V Adams wrote:
> Hannes
Hannes,
A bit inelegant, but it works. Try this:
mtext("Overall Title Row 2", outer=TRUE, line=-17)
mtext("Overall Title Row 3", outer=TRUE, line=-34)
Jean
capy_bara wrote on 10/23/2012 09:08:39 AM:
>
> Dear all,
> I have a 3x2 plot and in addition to the title of the individual plots I
>
Dear all,
I have a 3x2 plot and in addition to the title of the individual plots I
would like to have an overall title
for each row. I managed to get an overall title for the whole plot matrix
with mtext:
par(mfrow=(c(3,2)), mar=c(6.4,4.5,4.2, 1.8), oma=c(0,0,3,0))
for (i in 1:6)
barplot(sample
Dear R users,
I'm plotting 5 loess smooth lines in one paragraph. Since the publisher
does not print colorful pictures, I differentiate them by using different
line types. I'm wondering if there are other options to make the graph more
readable. It is really difficult for readers to tell the diffe
If you have a million levels is it really necessary to use a factor? I'm
not sure what advantages it will to have to a string in this circumstance
(especially since you don't seem to know the levels a priori but have to
learn them from the data).
Hadley
On Sunday, September 16, 2012, Sam Steingol
Hello,
The obvious simplification is to call union() only once. With 10M rows
it should save time.
Then I've asked myself whether unique() wouldn't be faster.
f1 <- function(x){
x[[1]] <- factor(x[[1]], levels = union(x[[1]], x[[2]]))
x[[2]] <- factor(x[[2]], levels = union(x[[1]], x
I have a data frame with columns which draw on the same underlying
universe, so I want them to be factors with the same level set:
--8<---cut here---start->8---
> z <- data.frame(a=c("a","b","c"),b=c("b","c","d"),stringsAsFactors=FALSE)
> str(z)
'data.frame':
I think multicore is one of answer if you can write your function in to lapply.
On Mon, Jun 18, 2012 at 12:14 PM, R. Michael Weylandt
wrote:
> I would argue (somewhat emphatically) that the parallel facilities you
> are looking at are absolutely not for `for` loops. `for` loops are a
> control st
I would argue (somewhat emphatically) that the parallel facilities you
are looking at are absolutely not for `for` loops. `for` loops are a
control structure native to imperative programming and, as such, are
inherently stateful. This provides many advantages, but easy
parallelization is absolutely
Thanks for all replied.
I read the introduction of R parallel. Is it for loops only?
Gary
On Sun, Jun 17, 2012 at 10:04 AM, R. Michael Weylandt <
michael.weyla...@gmail.com> wrote:
> Take a look at the parallel package which ships with all current versions
> of R.
>
> Michael
>
> On Jun 17, 2
On 17.06.2012 19:04, R. Michael Weylandt wrote:
Take a look at the parallel package which ships with all current versions of R.
which is the right answer for the body of the message. For the subject
line: Take a look at multi-threaded BLAS which can be used with R.
Uwe Ligges
Michael
O
Take a look at the parallel package which ships with all current versions of R.
Michael
On Jun 17, 2012, at 11:39 AM, Gary Dong wrote:
> Dear R users,
>
> I'm wonder if there is a easy way to make R use multi-CPUs on my computer.
> My computer has four CPUs but R uses only one. Thanks.
>
> G
Dear R users,
I'm wonder if there is a easy way to make R use multi-CPUs on my computer.
My computer has four CPUs but R uses only one. Thanks.
Gary
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https://stat.ethz.ch
Hi,
I understand that R can be used to plot correlated values using a
Multi-parameter histogram. We have authorization requests and response
and they are correlated because a response is governed by a SLA. Is it a
good use case for using R to correlate these requests and responses ?
Ar
thx, guys, almost there. This is good fodder for the vignette or ?parallel.
Steps:
(1) install package "snow" on all machines which you want to be part
of a cluster.
(2) run under R
library(parallel)
cl <- makeCluster(c("localhost", "calc.localdomain"), "SOCK")
result <- parLapply(cl=cl, X=1:10
On Sat, Apr 21, 2012 at 8:20 AM, ivo welch wrote:
> hi uwe---my box is different:
>
> cl <- makeCluster(c("localhost", "welch", "calc"), "SOCK")
> Error in loadNamespace(name) : there is no package called 'snow'
>
> this seems to be part of snow, not parallel. ok, install snow first,
> then rerun
On 21.04.2012 17:20, ivo welch wrote:
hi uwe---my box is different:
cl<- makeCluster(c("localhost", "welch", "calc"), "SOCK")
Error in loadNamespace(name) : there is no package called 'snow'
this seems to be part of snow, not parallel. ok, install snow first,
then rerun.
No, you just need
hi uwe---my box is different:
cl <- makeCluster(c("localhost", "welch", "calc"), "SOCK")
Error in loadNamespace(name) : there is no package called 'snow'
this seems to be part of snow, not parallel. ok, install snow first,
then rerun.
library(snow)
Attaching package: 'snow'
The following objec
On 21.04.2012 06:34, ivo welch wrote:
the vignette to the library(parallel) mentions snow repeatedly (esp
differences in its implementation in parallel from the original).
unfortunately, it doesn't give an example or tutorial for
multi-machine use with sockets.
could someone please point me to
the vignette to the library(parallel) mentions snow repeatedly (esp
differences in its implementation in parallel from the original).
unfortunately, it doesn't give an example or tutorial for
multi-machine use with sockets.
could someone please point me to a simple working example, where a
master
Dear R experts:
could someone please point me to a page that explains how to set up
more than 1 machine for library parallel (which is quickly becoming my
favorite!)
my dream setup would be a design where I just pass a list of
hostnames:user:password to my parallel master, and then start R
listen
Ok, I have a new, multipart problem that I need help figuring out.
Part 1. I have a three dimensional array (species, sites, repeat counts
within sites). Sampling effort per site varies so the array should be
ragged.
Maximum number of visits at any site = 22
Number of species = 161
Number of sit
It's easier to do log plots as
plot(h$density, log = L)
where L is one of "x", "y", or "xy" as you choose. This is well documented.
Michael
On Wed, Mar 14, 2012 at 12:02 AM, Sam Steingold wrote:
>> * David Winsemius [2012-03-13 17:53:14 -0400]:
>> On Mar 13, 2012, at 5:33 PM, Sam Steingold wr
> * David Winsemius [2012-03-13 17:53:14 -0400]:
> On Mar 13, 2012, at 5:33 PM, Sam Steingold wrote:
>> I can, of course, plot log(h$density), but then the number labels will
>> be wrong.
>
> You could try apply a log transform to the appropriate component of
> the "h" object and using barplot to
On Mar 13, 2012, at 5:33 PM, Sam Steingold wrote:
I have a vector x:
table(x)
2 3 4 5 6 7 8 9101112
1314
45547 11835 4692 2241 1386 820 593 425 298 239 176
158 115
1516171819202122232
I have a vector x:
table(x)
2 3 4 5 6 7 8 91011121314
45547 11835 4692 2241 1386 820 593 425 298 239 176 158 115
15161718192021222324252627
9488766747
On Mar 7, 2012, at 08:13 , Paul Johnson wrote:
> I want to write an R help example that throws up 2 graphs in separate
> windows, for comparison. In Linux I plot one, then run
>
> x11()
>
> to spawn a new on-screen device.
>
> Is there some generic equivalent so I can write an example that wil
I want to write an R help example that throws up 2 graphs in separate
windows, for comparison. In Linux I plot one, then run
x11()
to spawn a new on-screen device.
Is there some generic equivalent so I can write an example that will
work for Windows and Mac users as well?
If there is none, don'
rg [mailto:r-help-boun...@r-project.org] On
Behalf Of R DF
Sent: Monday, February 13, 2012 9:19 AM
To: r-help@r-project.org
Subject: [R] multi-regression with more than 50 independent variables
Hi R Users,
I am going to run a multiple linear regression with around 57 independent
variables. Each time I
Hi R Users,
I am going to run a multiple linear regression with around 57 independent
variables. Each time I run the model with just 11 variables, the results
are reasonable. With increasing the number of independent variables more
than 11, the coefficients will get “NA” in the output. Is there a
etween the screen device and
the file device.
--
David.
--- On Mon, 2/6/12, ilai wrote:
From: ilai
Subject: Re: [R] Multi-page PDF using dev.copy2pdf(filename,
onefile=TRUE)?
To: "Doug Hill"
Cc: r-help@r-project.org
Date: Monday, February 6, 2012, 12:24 PM
Doug,
dev.copy2pdf c
Thanks Elai, that did it! I never considered using any X11 options, as I'm on
Windows, and in the docs I read it sounded like X11 options only pertained to
the OSX/Linux/.. world. Thanks for your help, Doug
--- On Mon, 2/6/12, ilai wrote:
From: ilai
Subject: Re: [R] Multi-page PDF
Doug,
dev.copy2pdf closes the connection after it's "done", so onefile is
meaningless. To look at each plot before copy to a single pdf, you
could open a pdf(...) but revert between it and your graphic device:
graphics.off()
plot(1:7, 1:7)
x11c<- dev.cur() # your current graphics device
pdf(f
Hi all. I want to generate a sequence of n plots and save them into a single
PDF file, one plot per page. From the R docs and other sources I gather the
basic way to do this is save plot 1 into a file then append the 2:n plots to
the same file.
This code shows my basic approach, but for some re
I'm looking for an extension of kappa to measure agreement among multiple
raters when there can be more than one response per subject. For example,
say a group of doctors assign diseases to patients. Each patient will be
assigned one to many diseases, and the number of doctors assigning diseases
On Tue, Nov 8, 2011 at 1:04 PM, Ben quant wrote:
> Because I don't know anything about sqldf. :)
>
> Here is what happens, but I"m sure it is happening because I didn't read
> the manual yet:
>
>> s <- sqldf('create table r.dat("id" int primary key,"val" int)')
> Error in ls(envir = envir, all.nam
On Tue, Nov 8, 2011 at 11:43 AM, Ben quant wrote:
> Hello,
>
> I'm using package RpgSQL. Is there a better way to create a multi-line
> query/character string? I'm looking for less to type and readability.
>
> This is not very readable for large queries:
> s <- 'create table r.BOD("id" int primar
Because I don't know anything about sqldf. :)
Here is what happens, but I"m sure it is happening because I didn't read
the manual yet:
> s <- sqldf('create table r.dat("id" int primary key,"val" int)')
Error in ls(envir = envir, all.names = private) :
invalid 'envir' argument
Error in !dbPreExi
Why not just send it in as is. I use SQLite (via sqldf) and here is
the way I write my SQL statements:
inRange <- sqldf('
select t.*
, r.start
, r.end
from total t, commRange r
where t.comm = r.comm and
t.loc betw
Hello,
I'm using package RpgSQL. Is there a better way to create a multi-line
query/character string? I'm looking for less to type and readability.
This is not very readable for large queries:
s <- 'create table r.BOD("id" int primary key,"name" varchar(12))'
I write a lot of code, so I'm looki
It's usually standard to provide an example of what code you've tried
and also to put your data in a form that can be more easily
cut-and-pasted into R.
That said, would something like this work if you know you only have
two sorts of cross in each level?
lapply(spl, function(x) {x <- split(x[,1],
hi all
I have R object look like this:
> spl
$SB012XSB044
DPW Cross
1 66.6 SB012XSB044
2 96.5 SB012XSB044
3 78.8 SB012XSB044
4 68.6 SB012XSB044
5 62.0 SB012XSB044
6 72.1 SB044XSB012
7 72.2 SB044XSB012
8 69.6 SB044XSB012
9 87.9 SB044XSB012
10 84.4 SB044XSB012
11 51.9 SB044XSB012
I am not a Bayesian. In the non-Bayesian case you would use SUR to model both
equations simultaneously. If both use the exact same matrix of data, X
(i.e., the value are numerically absolutely identical), then SUR will
collapse to OLS. In that sense you get a "combined" estimate using SUR that
resp
Hi,
I have a question regarding the modeling methodology of the following problem:
* I have two data sets {X_i,y_i} {X_i,z_i}, i=1..N,
where y_i = f(X_i) + i.i.d. Gaussian noise
and z_i = g(X_i) + i.i.d. Gaussian noise
* I apply bayesian linear regression to each of them and obtain
p(y|X
Dear list,
I performed a multivariate analysis on freshwater invertebrates data. So
I obtained coordinates of my samples on the axes defining the first
factorial plane (F1 and F2).
I would like to see if the positions on my factorial plan could be
linked to levels of impairment ('low' vs 'signifi
Hi there,
Does anyone know if there is a package in R for multi-demensional
Gaussian quadrature? I checked out the package "gaussquad" but it can
only do 1D. Thanks!
Lei Liu
Associate Professor
Division of Biostatistics
Department of Public Health Sciences
University of Virginia School of Med
Hi,
Does anyone know of a package that implements Multi-task SVM in R? I found
one in Matlab :
http://www.ece.umn.edu/users/cherkass/predictive_learning/Resources/MTL_Software_Description.pdf
I was wondering if there is something similar in R?
Thank you for your help.
Sincerely,
Vishal
Dear all,
My name is Pedro Latorre Carmona and I work at the Computer Languages
and Systems Department of the Jaume I University in Castellon (Spain).
I get in contact with you because I am currently working in the
development of feature selection methods for "multi-output" regression
datase
On Sun, Apr 24, 2011 at 07:02:48PM -0400, Ravi Varadhan wrote:
> Julian,
>
> You have not specified your problem fully. What is the nature of f? Is f a
> scalar function or is it a vector function (2-dim)?
It's something like this (only a bit worse):
given x, work out alpha from
cos(alpha)
On Mon, Apr 25, 2011 at 12:57:46AM +0200, peter dalgaard wrote:
> > I have a set of data of the form (x, y1, y2) where x is the
> > independent variable and (y1, y2) is the response pair. The model is
> > some messy non-linear function:
> >
> > (y1, y2) = f(x; param1, param2, ..., paramk) + (y1e
If y1 and y2 are only dependent on x, can't you model them separately?
Joal Heagney
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide
t.net]
Sent: Sunday, April 24, 2011 6:25 PM
To: Julian Gilbey
Cc: r-help@r-project.org
Subject: Re: [R] Multi-dimensional non-linear fitting - advice on best method?
On Apr 23, 2011, at 8:38 PM, Julian Gilbey wrote:
> Hello!
>
> I have a set of data of the form (x, y1, y2) where x is the
On Apr 24, 2011, at 02:38 , Julian Gilbey wrote:
> Hello!
>
> I have a set of data of the form (x, y1, y2) where x is the
> independent variable and (y1, y2) is the response pair. The model is
> some messy non-linear function:
>
> (y1, y2) = f(x; param1, param2, ..., paramk) + (y1error, y2err
On Apr 23, 2011, at 8:38 PM, Julian Gilbey wrote:
Hello!
I have a set of data of the form (x, y1, y2) where x is the
independent variable and (y1, y2) is the response pair. The model is
some messy non-linear function:
(y1, y2) = f(x; param1, param2, ..., paramk) + (y1error, y2error)
where
Hello!
I have a set of data of the form (x, y1, y2) where x is the
independent variable and (y1, y2) is the response pair. The model is
some messy non-linear function:
(y1, y2) = f(x; param1, param2, ..., paramk) + (y1error, y2error)
where the parameters param1, ..., paramk are to be estimate
he i,j values so each cores
saves at the right place inside the lst matrix.
Could you please help me with that?
Regards
Alex
--- On Thu, 2/17/11, Ben Haller wrote:
> From: Ben Haller
> Subject: Re: [R] multi process support in R
> To: "Alaios"
> Cc: R-help@r-project.org
&
On Fri, Mar 4, 2011 at 6:48 AM, Joanna Lewis wrote:
> Dear R users,
>
> I have been using rsympy to solve a set of simultaneous equations from R.
> There are two solutions for the variable I'm interested in, xx[0] and xx[1],
> which are in terms of symbols called lam and conc. I'd like to pick out
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