similar to: Making tapply code more efficient

Suppose I have a dataframe as follows: dat <- data.frame(id = c(1,1,2,2,2), var1 = c(10,10,20,20,25), var2 = c('foo', 'foo', 'foo', 'foobar', 'foo')) Now, if I were to subset by id, such as: > subset(dat, id==1) id var1 var2 1 1 10 foo 2 1 10 foo I can see that the elements in var1 are exactly the same and the elements in var2 are exactly

Suppose I have the following data: tmp <- data.frame(var1 = sample(c(0:10), 3, replace = TRUE), var2 = sample(c(0:10), 3, replace = TRUE), var3 = sample(c(0:10), 3, replace = TRUE)) I can run the following double loop and yield what I want in the end (rr1) as: library(statmod) Q <- 2 b <- runif(3) qq <- gauss.quad.prob(Q, dist = 'normal', mu = 0, sigma=1) rr1 <- matrix(0,

I have constructed the function mml2 (below) based on the likelihood function described in the minimal latex I have pasted below for anyone who wants to look at it. This function finds parameter estimates for a basic Rasch (IRT) model. Using the function without the gradient, using either nlminb or optim returns the correct parameter estimates and, in the case of optim, the correct standard

Dear List: I am working to understand some differences between the results of the svymean() function in the survey package and from code I have written myself. The results from svymean() also agree with results I get from SAS proc surveymeans, so, this suggests I am misunderstanding something. I am never comfortable with "I did what the software" does mentality, so I am working to

Does anyone see why my code does not integrate to 1? library(statmod) mu <- 0 s <- 1 Q <- 5 qq <- gauss.quad(Q, kind='hermite') sum((1/(s*sqrt(2*pi))) * exp(-((qq$nodes-mu)^2/(2*s^2))) * qq$weights) ### This does what's it is supposed to myNorm <- function(theta) (1/(s*sqrt(2*pi))) * exp(-((theta-mu)^2/(2*s^2))) integrate(myNorm, -Inf, Inf)

I am using both nlminb and optim to get MLEs from a likelihood function I have developed. AFAIK, the model I has not been previously used in this way and so I am struggling a bit to unit test my code since I don't have another data set to compare this kind of estimation to. The likelihood I have is (in tex below) \begin{equation} \label{eqn:marginal} L(\beta) = \prod_{s=1}^N \int

Using ranef() (package nlme, version 3.1-75) with an 'lme' object I can obtain random effects for intercept and slope of a certain level (say: 1) - this corresponds to (say level 1) "residuals" in MLWin. Maybe I'm mistaken here, but the results are identical. However, if I try to get the standardized random effects adding the paramter "standard=T" to the

Dear List: It appears that simulating data where all dataframes are stored as a list will only work for relatively small analyses. Instead, it appears that creating N individual dataframes, saving them, and loading them when needed is the best way to save memory and make this a feasible task. As such, I now have a new(er) question with respect to dealing with individual files within a loop. To

Can anyone point me to examples with R code where bwplot in lattice is used to order the boxes in ascending order? I have found the following discussion and it partly works. But, I have a conditioning variable, so my example is more like bwplot(var1 ~ var2|condition, dat) Th example in the discussion below works only when there is not a conditioning variable as far as I can tell. I can tweak the

Searched archives and found some old email threads on the topic. But mot exactly what I think I need. Suppose I have a datafile such as tmp. tmp <- data.frame(var1 = c(rnorm(1000), rnorm(1000, 1, 1)), var2 = gl(2, 1000)) I'd like a plot similar to the one below, but with an abline of v=0 in the lower panel and v=1 in the upper panel. Code below creates two lines in each panel, not quite

Hi. On Wed, 08 Mar 2023 22:21:28 +0100 Tomasz Chmielewski via rsync wrote: > After upgrading to rsync 3.2.7, the following command hangs forever > (using "--usermap" causes the hang; without "--usermap" it doesn't > hang): > rsync -v -p -e --usermap user:user /etc/services user at remote: This command is incorrect: the -e option needs a command. Without

I have been timing a particular model fit using lmer on several different computers and came up with a peculiar result - the model fit is considerably slower on a dual-core Athlon 64 using Goto's multithreaded BLAS than on a single-core processor. Here is the timing on a single-core Athlon 64 3000+ running under today's R-devel with version 0.995-5 of the Matrix package. >

Suppose I have data such as the following set.seed(12345) tmp <- data.frame(var1 = rnorm(100), var2 = rnorm(100), var3=rnorm(100, 10, 30)) tmp1 <- data.frame(vars = with(tmp, c(var1, var2, var3)), type = gl(3, 100)) var3 is on a different scale, but I create the following plot, which looks terrible as a result bwplot(~ vars|type, tmp1, layout = c(1,3), ) Of course, I can

Dear R-list, maybe someone can help me with the following mixed-effects models problem, as I am unable to figure it out with the 'nlme-bible'. I would like to fit (in R, obviously) a so-called animal model (google e. g. "Heritability and genetic constraints of life-history" by Pettay et al.) to estimate the variance component that is due to genetic effects. The covariances of

Hi Linfeng, On 05/06/17 03:31 PM, Linfeng Zhang wrote: > Yes we'll have one more patch set related to xcorr in next week. Please > don't wait if it's too late for 1.2 release. Assuming there's no issue with the patches, next week isn't too late. Also, I've started looking at your patches. So far there's one thing that puzzles me a bit. In the OPUS_CHECK_ASM

> I am not a regular samba developer, but I wanted to have psexec > equivalent, so I wrote it, it works but still need some development. > I do not know if patches of such sizes (about 30k) are welcome on > this list so I've put it on web page, with some description: > http://eol.ovh.org/winexe/ > Comments welcome. Hi, this is really great, you can get Windows command

Tried that. It rebuilds index based on dovecot-uidlist. But not the dovecot-uidlist based on actual mail data. :( Fil On March 21, 2018 11:58:21 PM EDT, "@lbutlr" <kremels at kreme.com> wrote: >On 2018-03-21 (17:15 MDT), Dmitry Filonov ><filonovd at enders.tch.harvard.edu> wrote: >> Now the question is if there's any way to tell dovecot to rebuild

Hi everyone, I would like to ask a question regarding to the data used to fit the mixed model. I wonder that, for the response variable data used to fit the mixed model (either via "spm" or "lme"), we must have several observations per subject (i.e. Yij, i = 1,..,M, j = 1,.., ni) or it can be just one observation per subject (i.e. Yi, i = 1,...,M). Since we have to

Hola, Esta pregunta la hice en stackoverflow <http://stackoverflow.com/questions/31137940/randomly-assign-teachers-to-classrooms-imposing-restrictions/31143808#31143808>pero nadie pudo contestarla. 1. Quiero generar N escuelas, con G grados y C divisiones. 2. Quiero asignar cada uno de T maestros a 2 divisiones en un grado y escuela Si tengo C=4 divisiones, puedo lograr lo que quiero con

Hola, 0. La falta de 'elegancia' hace que sea mas dificil hacer cambios al codigo. Por ejemplo cambiar n.classrooms <- 4 a n.classrooms <- 20 1. Cuando tengo solo 4 puedo hacer esto: schoolGrade$A <- Teachers$Teacher.ID[1:cuttoff1] schoolGrade$B <- Teachers$Teacher.ID[1:cuttoff1] schoolGrade$C <- Teachers$Teacher.ID[(cuttoff1+1):n.teachers] schoolGrade$D <-