similar to: annotate histogram

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

Dear R team, As this is a university email address with very small inbox limit, can I please change my R email subscription to another email address instead of this one? My new email address is wendy2.qiao@gmail.com. I have change my email in my profile, but seems that does not change my subscription. Thank you. Wendy [[alternative HTML version deleted]]

Hi all, I have a huge matrix of TRUE/FALSE table like following, and I want to count the number of TRUEs in each row. Instead of looping through each row and do length(Z[Z==TRUE]), I am wondering if there is an easier way of doing this. [,1] [,2] [,3] [1,]TRUE FALSE FALSE [2,]FALSE TRUE TRUE Thank you in advance. Wendy -- View this message in context:

Dear All I recently proposed a simple modification to Wedderburn's 1974 estimate of overdispersion for count and binomial data, which is used in glm for the quasipoisson and quasibinomial families (see the reference below). Although my motivation for the modification arose from considering sparse data, it will be almost identical to Wedderburn's estimate when the data are not sparse.

Hi, Please could somebody has any information about the following package: IlluminaGUI, published here: http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btm101v1 The link given in the article is dead and authors doesn't reply ! Is there someone who uses it ? Thank you very much for help -- View this message in context:

Hi all, I am trying to plot the fitted trajectories for each individual from an individual growth model (fit with a linear mixed effects model in lme). How can I plot each person's trajectory in the *same* panel, along with the mean-level trajectory? Below is an image of a plot similar to what I'm trying to create (from: http://jpepsy.oxfordjournals.org/content/31/10/1002/F6.large.jpg):

Hello. I want to specify a diagonal structure for the covariance matrix of random effects in the lme() function. Here is the call before I specify a diagonal structure: > fit2<-lme(Ln.rgr~I(Ln.nar-log(0.0011)),data=meta.analysis, + random=~1+I(Ln.nar-log(0.0011)|STUDY.CODE,na.action=na.omit) and this works fine. Now, I want to fix the covariance between the between-groups slopes

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi :) Is there any plan to include delivery agent in 1.x? I would be very happy, if there would be lmtp delivery agent included with dovecot 1.x... This would make creating large mailsystem cluster creation very simple + indexes would be always up2date. Brane -----BEGIN PGP SIGNATURE-----

Hi all, I have a list of numbers, e.g., X = c(60593.23, 71631.17, 75320.1), and want to round them so the output is Y = c(60000, 80000, 80000). I tried Y<-round(X,-4), but it gives me Y = c(60000, 70000, 80000). Do anybody know how to round up a number to 10^4? Thank you in advance. Wendy -- View this message in context:

>>>>> akshay kulkarni >>>>> on Wed, 31 May 2023 20:55:33 +0000 writes: > dear members, > I am using arfima() from forecast package to model a time > series. The following is the code: >> LYGH[[202]] > [1] 45.40 3.25 6.50 2.15 >> arfima(LYGH[[202]]) > Error in .fdcov(x, fdf$d, h, nar = nar, nma = nma,

dear members, I am using arfima() from forecast package to model a time series. The following is the code: > LYGH[[202]] [1] 45.40 3.25 6.50 2.15 > arfima(LYGH[[202]]) Error in .fdcov(x, fdf$d, h, nar = nar, nma = nma, hess = hess, fdf.work = fdf$w) : NA/NaN/Inf in foreign function call (arg 5) I tried viewing .fdcov() with the following code:

Dear Martin, Sad that the bug is beyond your ken... Fortunately, the error happens only rarely...The length of LYGH was 719 and there were only two such errors..I will just replace them with NA and make do. By the by, what if I send LYGH as an attachment to your actual mail ( not the r-help mail)? Will it help? Can you then pinpoint the cause? Or should I raise a bug

I was sniffing in the fracdiff library (this is for fractionally integrated ARMA processes; Haslett and Raftery 1989). The documentation suggests that one tries the following simple example: library(fracdiff) ts.test <- fracdiff.sim( 5000, ar = .2, ma = -.4, d = .3) fracdiff( ts.test$series, nar = length(ts.test$ar), nma = length(ts.test$ma)) When I run this, I get the following error: R

Dear all, Can I do a permutation test if the number of individuals in one group is much bigger than in the other group? I searched the literature but I didin´t find any assumption that refers to this subject for permutation tests. Best regards João Fadista Ph.d. student UNIVERSITY OF AARHUS Faculty of Agricultural Sciences Dept. of Genetics and Biotechnology Blichers Allé 20, P.O.

Hello useRs (please don't kill me), I've fairly new to R having only a few months of playing around with R. What little I've learned has been extremely useful. If someone could point me as to how to replicate the Boltzman Sigmodial curve fit as provided by Graphpad software I'd be eternally grateful. Where we currently use Graphpad for only this one function,its seems highly

Hello, I recently began using R and the lme4 package to carry out linear mixed effects analyses. I am interested in the effects of variables 'prime','time', and 'mood' on 'reaction_time' while taking into account the random effect 'subjects.' I've read through documentation on lme4 and came up with the following formula for use with lmer:

Dear time-series specialist: I've got some time series representing measurements from a physical process, like atomic decay data. These time series look almost random, but should hopefully be distinguishable as they were taken under different conditions. I am looking for statistical approaches that are sensitive enough to discriminate between such series of measurements. Preferably, there

If you mean this paper by Fahrmeir: http://biomet.oxfordjournals.org/cgi/content/abstract/81/2/317 I would recommend BayesX: http://www.stat.uni-muenchen.de/~bayesx/. BayesX interfaces with R and estimates discrete (and continuous) time survival data with penalized regression methods. If you are looking for a bona fide Bayesian survival analysis method and do not wish to spend a lot of time

Does anyone know how to plot mismatch distributions in R, in order to look similar to : http://mbe.oxfordjournals.org/content/20/1/76/F7.large.jpg -- View this message in context: http://r.789695.n4.nabble.com/Plot-mismatch-distributions-in-R-tp3554850p3554850.html Sent from the R help mailing list archive at Nabble.com.

This is the named article: http://ije.oxfordjournals.org/content/37/5/1161.long maybe it can help you to help me... :-( -- View this message in context: http://r.789695.n4.nabble.com/INSTRUMENTAL-VARIABLES-WITH-BINARY-OUTCOMES-tp4642361p4642363.html Sent from the R help mailing list archive at Nabble.com.