similar to: how to show a section of a matrix neatly (or row by row ) that satisfies some condition

Hi all, I want to show the rows of a matrix (100x3) of which some of its elements satisfy a certain condition. In particular, how can I display the 2 rows of my matrix one after the other and not all all elements of column 1 first, then column 2 and so on. See the following. > finest[finest[,1] > 10^3] [1] 4.960632e+13 3.612619e+04 7.668204e+12 1.001911e+04 8.886153e-01 [6]

Dear R-listers, I am writing a function that will generate a simple plot for the user . The size of the window (that contains the plot) may not be what the user wants. Supposing the user adjusts the window to a size of her/his choice, I would like to be able to save the new window size and specify the plot to be of this new window size when the user calls my function again. My question is

Dear R-listers, I have been using Snowfall (version 1.84) for parallel computing on a quad-PC running Windows 7 for a month or so without much problem. I started having problems runnnig R with Snowfall over our network when a new Novell client was installed for Windows 7. I experinenced network mapping problem with this new client. Our network colleague provided a fix which worked but a little

Dear R-listers, I am fitting bivariate mixed models for cost-effectiveness data of cluster randomized trials using lme in R. So I have individuals nested within clusters. My response variable is a vector with bivariate response (individual level costs and effects) stacked into a single column. The covariates in my models are a constant and a treatment term. They are response-specific, e.g. a

Dear all, I need to read in 4 sets of tab delimited data in a loop. The 4 data sets are called "simu1.dat", "simu2.dat" and so on. I know what I need on the righthand side of the read.table expression but I can't the left hand side of it to work (see the line in bold below). Can you kindly help? Many thanks. simu1 <- matrix(0,30,3) simu2 <- matrix(0,30,3) simu3

Dear all, I found a problem with 'lme4'. Basically, once you load the package 'aod' (Analysis of Overdispersed Data), the functions 'lmer' and 'glmer' don't work anymore: library(lme4) (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) (gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd), family = binomial, data

Dear all, I'm trying to estimate the parameters of a special case of a poisson model, where the specified equation has an integral and several fixed parameters. I think that the MLE command in STATS4 package could be a good choice, but it's a little complicated. I've got some problems with the offset and I don't understand some of the functions. Do you know where can I find some

Hello, I'm trying to save a graph as a .ps file to include it in a LaTex presentation, but R replies: Error: Invalid font type In addition: Warning messages: 1: font family not found in PostScript font database 2: font family not found in PostScript font database If I load the package grDevices and type "postscript()" then I can save it, but it creates also a text file saying:

Dear all, I have a very basic question: how does the logLik function work for poisson models? Example: I simulate 20 observations from a Poisson distribution with mean 800. y <- rpois(20,800) model <- glm(y ~ 1, family=poisson()) logLik(model) I would like to know what's the exact formula the function logLik uses. I looked at ?extractAIC but I cannot sort it out. Can you please

Dear Wolfgang Viechtbauer and R users, I have few questions regarding the development of the package 'metafor. As you suggested , I post to the R-help mailing list. I read you're planning an extension of this method to the multivariate case. I think it would be a useful tool. I'm currently performing some analyses with R on multiple outcomes, using the Stata command mvmeta to get

Dear fellows, I'm trying to extract the AIC statistic from a GLM model with quasipoisson link. The formula I'm referring to is AIC = -2(maximum loglik) + 2df * phi with phi the overdispersion parameter, as reported in: Peng et al., Model choice in time series studies os air pollution and mortality. J R Stat Soc A, 2006; 162: pag 190. Unfortunately, the function logLik

Dear all, I've tried to solve the Es. 12, cap 4 of "Introduction to GLM" by Annette Dobson. It's about the relationship between survival time of leukemia patients and blood cell count. I tried to fit a model with exponential distribution, first by glm (family gamma and then dispersion parameter fixed to 1) and then with survreg. They gave me the same point estimates but the

Dear R users, I'm trying to specify a generalized linear mixed model in R, basically a Poisson model to describe monthly series of counts in different regions. My aim is to fit subject-specific curves, modelling a non-linear trend for each region through random effects for linear splines components (see Durban et al, Stat Med 2005, or " Semiparametric regression" by Ruppert et al,

Dear R Community, I am pleased to announce the release of a new package called 'dlnm', now available on CRAN (version 0.2.1). The package dlnm provides some facilities to run distributed lag models (DLM's) and their non-linear extension (DLNM's), a modelling framework to describe simultaneously non-linear and delayed effects between predictors and an outcome in time-series

Dear R Community, I am pleased to announce the release of a new package called 'dlnm', now available on CRAN (version 0.2.1). The package dlnm provides some facilities to run distributed lag models (DLM's) and their non-linear extension (DLNM's), a modelling framework to describe simultaneously non-linear and delayed effects between predictors and an outcome in time-series

Hello R users, I'm trying to understand the meaning of the results returned by the command 'predict' with type="terms". I thought it was the matrix with the fitted values for each term (value of predictor * related coef), but the calculation is different. I include an example below: y <- rnorm(10) x1 <- rnorm(10) x2 <- rnorm(10) model <- lm(y ~ x1 + x2)

Hello R users, I'm trying to solve an apparently simple problem. I include a matrix in a model formula, and I want then to extract the related coefficients. Basically, I want a function func such that: mymatrix <- cbind(rnorm(10),rnorm(10)) y <- b <- rnorm(10) model <- lm(y ~ b + mymatrix) func(mymatrix,model) which returns only the 3rd and 4th coefficients. I thought to

Hello, I have compared the potentials of R and Stata about GLMM, analysing the dataset 'ohio' in the package 'faraway' (the same dataset is analysed with GEE in the book 'Extending the linear model with R' by Julian Faraway). Basically, I've tried the 2 commands 'glmmPQL' and 'glmer' of R and the command 'xtmelogit' of Stata. If I'm not

https://bugs.freedesktop.org/show_bug.cgi?id=28107 Summary: [NV31] Product: xorg Version: unspecified Platform: x86 (IA32) OS/Version: Linux (All) Status: NEW Severity: normal Priority: medium Component: Driver/nouveau AssignedTo: nouveau at lists.freedesktop.org ReportedBy: finest.bug at

Dear Gustaf, I wish you a happy new year! I am a PhD Staff at LSHTM and I have been trying to use WHO anthro macros in R with the file you posted on internet but when I double check the WHZ, HAZ, WAZ output with output from ENA or STATA, it differs slightly. Do you have any idea why that might be the case? Many thanks Severine