On Tue, 16 Feb 2010, Lam, Tzeng Yih wrote:
Dear Dr. Turner,
Thank you very much for taking the time to answer my request. The suggestion
that you have provided did ring a bell for me. So, I went digging a bit and
found the following article that I have read a while ago:
Baskerville, G.L. 197
Whoops, forgot to cc. the list...
-pd
Myrland Øystein wrote:
> Dear R-help list,
>
>
>
> I have grouped data, looking like this:
>
>
>
> cases <- c(23,12,56,81)
>
> total <- c(123,234,248,390)
>
> x1 <- c(0,0,1,1)
>
> x2 <- c(0,1,0,1)
>
>
>
> Data <- as.data.frame(cbind(cases,total
Hi Doug,
Thanks. Next time I will post it to the R-SIG0-mixed-models mailing
list, as you suggested.
With respect to your question, the answer is no, these parameters do
not make sense. Here is the Stata output from "exactly" the same
model:
. xi:xtlogit inftmort i.cohort, i(code)
i.cohort
This is similar to another question on the list today.
On Tue, Feb 16, 2010 at 4:39 AM, Luisa Carvalheiro
wrote:
> Dear R users,
>
> I am having problems using package lme4.
>
> I am trying to analyse the effect of a continuous variable (Dist_NV)
> on a count data response variable (SR_SUN) usin
Hi,
On Fri, Feb 12, 2010 at 3:00 PM, Amy Hessen wrote:
>
> Hi,
> Every time I run a svm regression program, I got different RMSE value.
> Could you please tell me what the reason for that?
Sorry, your question is a bit vague.
Can you provide an example/code that shows this behavior? Is the
diff
> It seems to me that R returns the unpenalized log-likelihood for the
> ratio likelihood test when ridge regression Cox proportional model is
> implemented. Is this as expected?
It is easy to verify that this is correct:
> fit1 <- coxph(Surv(time, status) ~ ridge(age) + ph.ecog, lung)
> fit2 <- c
On Tue, Feb 16, 2010 at 9:05 AM, Shige Song wrote:
> Dear All,
> I am trying to fit a 2-level random intercept logistic regression on a
> data set of 20,000 cases. The model is specified as the following:
> m1 <- glmer(inftmort ~ as.factor(cohort) + (1|code), family=binomial, data=d)
> I got
Hello
On 2/16/10, julien cuisinier wrote:
> 1. apply Vs for loop
>
> >> Seems apply is (was?) supposed to be faster than using for loop, some
> posts mention that it is now more of a cosmetic function (wrapper for "for
> loop") making the code essentially neater. Any thoughts/opinion/experien
On 16.02.2010 15:18, Pauline Haleux (JIC) wrote:
Dear all,
I am a total beginner in R, so sorry if this is the wrong place. I am using R
2.10.1 on a Mac (Mac OS 10.6.2).
I have this small dataset :
growth sugar
75 C
72 C
73 C
61 F
67
Dear All,
I am trying to fit a 2-level random intercept logistic regression on a
data set of 20,000 cases. The model is specified as the following:
m1 <- glmer(inftmort ~ as.factor(cohort) + (1|code), family=binomial, data=d)
I got "Warning message: In mer_finalize(ans) : false convergence (8)
Dear All,
I am trying to fit a 2-level random intercept logistic regression on a
data set of 20,000 cases. The model is specified as the following:
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the pos
Dear all,
I am a total beginner in R, so sorry if this is the wrong place. I am using R
2.10.1 on a Mac (Mac OS 10.6.2).
I have this small dataset :
growth sugar
75 C
72 C
73 C
61 F
67 F
64 F
62 S
63
Hi all,
I am working on a filled contour plot which shows a triangular matrix data
set (as shown below). Is there a possibilty to draw a triangular filled
contour in a equilateral triangle (like a ternary plot)?
Thanks in advance
Johannes
http://n4.nabble.com/file/n1557386/Bild3.png
--
View
But since you don't, why not calculate the density directly for each
point (e.g., in a loop). The formula is simple enough:
mean(dnorm(x-gx,sd=h1)*dnorm(y-gy,sd=h2))
yes, this was my initial thought, and it works. (But i was hoping kde2d or
some similar function could do it faster). I'l try
Also try
igraph
Stephen C. Upton
Research Associate
SEED (Simulation Experiments & Efficient Designs) Center for Data Farming
Naval Postgraduate School
> From: William Revelle
> Date: Mon, 15 Feb 2010 13:57:19 -0600
> To: Oliver Kullmann ,
> Subject: Re: [R] tree-drawing in R ?
>
> try
>
>
Dear Dr. Zeileis,
Thank you for pointing out on the maximum likelihood estimator property as well
as the delta method to obtain the standard error of estimated Theta.
I agree with you in that whether getting the standard error of estimated Theta
is useful or not. I will think about this further
Hi,
I have the following code snippet:
require(lattice)
f.barchart <- function(...) {
barchart(...,
panel = function(x, y, ...) {
panel.barchart(x, y, ...)
}
)
}
x <- data.frame(a = c(1,1,2,2), b = c(1,2,3,4), c = c(1,2,2,1)
Dear Dr. Turner,
Thank you very much for taking the time to answer my request. The suggestion
that you have provided did ring a bell for me. So, I went digging a bit and
found the following article that I have read a while ago:
Baskerville, G.L. 1972. Use of logarithmic regression in the estima
say you read the quantity.csv file into a variable called
'quantity'... similarly, 'equity_price.csv' to equity.
sweep(equity, 2, quantity, "*")
b
On Tue, Feb 16, 2010 at 11:20 AM, Sarah Sanchez
wrote:
> Dear Madam / R helpers,
>
> Unfortunately the solution you have suggested is not working in
On Tue, 16 Feb 2010 08:00:09 -0500 Esmail wrote:
> And along the same lines, any type of interactive debugging
> utility for R?
See this article in R News:
'Debugging Without (Too Many) Tears'
http://cran.r-project.org/doc/Rnews/Rnews_2003-3.pdf#page=29
--
Karl Ove Hufthammer
On Tue, 16 Feb 2010 03:36:17 -0800 (PST) geir
wrote:
> I want the density estimates for the points in a k x 2 matrix like for
> example
>
> A=[(0,7,0.3),(0.1,0.2),...,(0.5,0.9)]^T
>
> which is not equally spaced, (and i do not need the density of every
> combin
Yoni Schamroth-3 wrote:
>
>
> We are currently using the odbcConnect and odbcDriverConnect functions of
> RODBC package to connect to a DB built on SQL Server 2005.
> Are there any other packages / drivers/ methodology that may provide a
> faster connection?
>
Dates back to 1997: for SQL Ser
library(chron)
#untested
as.chron(paste(tdata[,"date"], tdata[,"time"]), "%Y/%m/%d %H:%M")
On Tue, Feb 16, 2010 at 4:47 AM, Alex Anderson
wrote:
> Hi All,
> I am attempting to work with some data from loggers. I have read in a .csv
> exported from MS Access that already has my dates and times (in
Dear Madam / R helpers,
Unfortunately the solution you have suggested is not working in the sense that
the quantities are not multplying the rows but its multiplying columnwise and
hence I am getting all wrong results.
I am again submitting my problem. Please guide me.
I have two input file
Dear all,
I know this topic has already been covered in other posts (at least the for
loop Vs apply family of function), but I am looking for fresh / up-to-date
opinion and feedback on those 3 methods to run unavoidable loops in R. I
realise that it may be too general question for many, so an
Hi All,
I am attempting to work with some data from loggers. I have read in a
.csv exported from MS Access that already has my dates and times (in 24
clock format), (with StringsAsFactors=FALSE).
> head(tdata)
LogData date time
177.16 2008/04/24 02:00
261.
Dear R-help,
I am having problems using package lme4.
I am trying to analyse the effect of a continuous variable (Dist_NV)
on a count data response variable (SR_SUN) using Poisson error
distribution. However, when I run the model:
summary(lmer((SR_SUN)~Dist_NV + (1|factor(Farm_code)) ,
family=p
Good morning .. sorry if this is a basic question, but is there
a lint-like utility for R to check for suspicious language
constructs?
And along the same lines, any type of interactive debugging
utility for R?
My main use of R is under Linux (though I run code sometimes
under Window XP). R versi
Hi,
We are currently using the odbcConnect and odbcDriverConnect functions of
RODBC package to connect to a DB built on SQL Server 2005.
Are there any other packages / drivers/ methodology that may provide a faster
connection?
Any help or advice would be appreciated.
Thanks
[[alterna
Trafim Vanishek posted a similar problem: "Joint density approximation?"
(without any solution for kde2d). Here is an example to illustrate my
problem.
Originally data is for example:
a=runif(10) (yes, the number of data should be larger)
b=runif(10)
c=kde2d(a,b,n=10,lims=c(0,1,0,1))
attach(c
vaibhav dua wrote:
>
> Hi,
>
> I'm trying to fit nonlinear mixed effects model using nlme function but
> getting an error message. Here is what I have:
>
> fitted_model = nlme(scores~spline(b1,b2,b3,kt,time),
>fixed = list(b1~1, b2~1, b3~1, kt~1),
>random = b1+b2+b3~1,
On 2010-02-16 1:24, Kum-Hoe Hwang wrote:
Howdy, R Grues
I have enjoyed R, but I cannot solve one problem easily. Please help my problem.
When I tried the R script, I got the following Error. This error
results from input data file exported through a Excel spreadsheet
software.
Error in step(l
Alex Levitchi wrote:
Hello
I am very thankful for the reply from Jim Holtman and David Winsemius, especially for the understandable explanations. it really works.
Now I get another problem I cannot figure out.
That is the situation:
I work in biology. I need to download several files according
Dear all,
I am using "penalized" package for "Ridge" regression. I do
not know how can I get regression coefficients using that package . Please
help me.
Thanks
--
Linda Garcia
[[alternative HTML version deleted]]
__
R-help@r
Hi Kum,
If you look at the code step function ( by typing step in the R
console), the condition (if (length(fit$residuals) != n) ) is not
fulfilled, this explains the error!
i hope this can help
Regards
M
Kum-Hoe Hwang a écrit :
Howdy, R Grues
I have enjoyed R, but I cannot solve one
Hi there,
I'm a PhD student investigating growth patterns in fish. I've been using the
minpack.lm package to fit extended von Bertalanffy growth models that include
explanatory covariates (temperature and density). I found the nls.lm comand a
powerful tool to fit models with a lot of parameters
Dear R users,
I am having problems using package lme4.
I am trying to analyse the effect of a continuous variable (Dist_NV)
on a count data response variable (SR_SUN) using Poisson error
distribution. However, when I run the model:
summary(lmer((SR_SUN)~Dist_NV + (1|factor(Farm_code)) ,
family=
I never had seen spline() inside some nls()/nlme() function. Are you sure
that this fit is possible? Splines makes a lot or successive local
polynomial fits, so they need a lot of parameters. I don't think that is
possible a good spline fit with only four parameters. In this case you could
use loe
Hello
I am very thankful for the reply from Jim Holtman and David Winsemius,
especially for the understandable explanations. it really works.
Now I get another problem I cannot figure out.
That is the situation:
I work in biology. I need to download several files according to an experiment,
w
Gabor Grothendieck wrote:
> On Mon, Feb 15, 2010 at 11:24 AM, David Winsemius
> wrote:
>> On Feb 15, 2010, at 11:01 AM, hadley wickham wrote:
>>
I, personally, utilize the ifelse(test,statement,statement) function when
possible over the methodology outlined.
>>> if + else and ifelse perf
one approach is:
Data.long <- with(Data, data.frame(
w = c(rbind(total - cases, cases)),
y = rep(0:1, nrow(Data)),
x1 = rep(x1, each = 2),
x2 = rep(x2, each = 2)
))
I hope it helps.
Best,
Dimitris
Myrland Øystein wrote:
Dear R-help list,
I have grouped data, looking lik
>
> I apologize for not including my entire script. What I typed into the shell
> was:
>
> *download.packages(ape)*
>
> to which R responded with a Tcl/Tk interface allowing me to set my CRAN.
> After I did so it proceeded to spit out the following error:
>
> *Loading Tcl/Tk interface ... done*
> E
Dear R-help list,
I have grouped data, looking like this:
cases <- c(23,12,56,81)
total <- c(123,234,248,390)
x1 <- c(0,0,1,1)
x2 <- c(0,1,0,1)
Data <- as.data.frame(cbind(cases,total,x1,x2))
Data
I would like to run a logistic regression with group weights on these,
where cases
Howdy, R Grues
I have enjoyed R, but I cannot solve one problem easily. Please help my problem.
When I tried the R script, I got the following Error. This error
results from input data file exported through a Excel spreadsheet
software.
Error in step(lm(pop.rate ~ as.numeric(year) + as.factor(po
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