similar to: maximization help :

G'day, All. I have been trying to trackdown a problem in my R analysis script. I perform a scale() operation on a matrix then do further work. Is there any way of inverting the scale() such that sX <- scale(X) Xprime <- inv.scale(x); # does inv.scale exist? resulting in Xprime_{ij} == X_{ij} where Xprime_{ij} \in R There must be some way of doing it but I'm such a newb

Dear people, I'm trying to do some analysis of a data using the models by Royle & Donazio in their fantastic book, particular the following function: http://www.mbr-pwrc.usgs.gov/pubanalysis/roylebook/panel4pt1.fn that applied to my data and in the console is as follows: > `desman.y` <- structure(c(3L,4L,3L,2L,1L), .Names = c("1", "2", "3",

I am trying to calculate Bayesian Credible Intervals for a proportion (disease prevalence values to be more specific) and am having trouble using R to do this. I am working with ncredint() function but have not had success with it. Please help! Example: Positive samples = 3 Total sampled = 10 Prevalence = 0.3 pvec <- seq(1,10,by=1) npost = dbinom(pvec,10,prob=0.3, log=FALSE) ncredint(pvec,

I'd like to pick up this thread started on 2019-04-11 (https://hypatia.math.ethz.ch/pipermail/r-devel/2019-April/077632.html). Modulo all the other suggestions in this thread, would my proposal of being able to disable forked processing via an option or an environment variable make sense? I've prototyped a working patch that works like: > options(fork.allowed = FALSE) >

Dear R experts Sorry for this question M1 <- 1:10 lcd1 <- c(11, 22, 33, 44, 11, 22, 33, 33, 22, 11) lcd2 <- c(22, 11, 44, 11, 33, 11, 22, 22, 11, 22) lcd3 <- c(12, 12, 34, 14, 13, 12, 23, 23, 12, 12) #generating variables through sampling pvec <- c("PR1", "PR2", "PR3", "PR4", "PR5", "PR6", "PR7",

On 03/11/2016 08:30 AM, Minchan Kim wrote: > Procedure of page migration is as follows: > > First of all, it should isolate a page from LRU and try to > migrate the page. If it is successful, it releases the page > for freeing. Otherwise, it should put the page back to LRU > list. > > For LRU pages, we have used putback_lru_page for both freeing > and putback to LRU

On 03/11/2016 08:30 AM, Minchan Kim wrote: > Procedure of page migration is as follows: > > First of all, it should isolate a page from LRU and try to > migrate the page. If it is successful, it releases the page > for freeing. Otherwise, it should put the page back to LRU > list. > > For LRU pages, we have used putback_lru_page for both freeing > and putback to LRU

Dear helpers, I am using R version 2.5.1 to estimate a multinomial logit model using my own maximum likelihood function (I work with share data and the default function of R cannot deal with that). However, the computer (I have an Athlon XP 3200+ with 512 GB ram) takes quite a while to estimate the model. With 3 categories, 5 explanatory variables and roughly 5000 observations it takes 2-3 min.

If I understand the thread correctly this is an RStudio issue and I would suggest that the developers consider using pthread_atfork() so RStudio can handle forking as they deem fit (bail out with an error or make RStudio work). Note that in principle the functionality requested here can be easily implemented in a package so R doesn?t need to be modified. Cheers, Simon Sent from my iPhone

On 04/10/2016 03:27 PM, Fabien Tarrade wrote: > Hi Duncan, >> Didn't you post the same question yesterday? Perhaps nobody answered >> because your question is unanswerable. > sorry, I got a email that my message was waiting for approval and when I > look at the forum I didn't see my message and this is why I sent it > again and this time I did check that the

Hi Group, Here is some data. p <- runif(1000) # sample data groups <- rep(c(1,2),each=500) #conditioning variable mydata <- cbind(p,groups) n <- length(p) u <- (1:n)/(n + 1) # uniform distribution reference for qqplot logp <- -log(p,base=10) logu <- -log(u,base=10) qqplot(logp,logu) How can I make the above qqplot in lattice and/or ggplot2. The sample is uniform, and I take

how do I check the rank of a matrix ? say A= 1 0 0 0 1 0 then rank(A)=2 what is this function? thanks I did try help.search("rank"), but all the returned help information seem irrelevant to what I want. I would like to know how people search for help information like this. rank(base) Sample Ranks SignRank(stats) Distribution of the

> On Jan 10, 2020, at 3:10 PM, G?bor Cs?rdi <csardi.gabor at gmail.com> wrote: > > On Fri, Jan 10, 2020 at 7:23 PM Simon Urbanek > <simon.urbanek at r-project.org> wrote: >> >> Henrik, >> >> the example from the post works just fine in CRAN R for me - the post was about homebrew build so it's conceivably a bug in their libraries. > > I

Henrik, the example from the post works just fine in CRAN R for me - the post was about homebrew build so it's conceivably a bug in their libraries. That's exactly why I was proposing a more general solution where you can simply define a function in user-space that will issue a warning or stop on fork, it doesn't have to be part of core R, there are other packages that use fork() as

I have a question, I generated some data and tried survreg to analyze them, but here, I want to get the covariance matrix of the coefficients. I know how to get corr from survreg, say, summary(f,corr=T), but how to get covariance matrix of the coefficient ? can I put them in a matrix and output ? thanks below is what I did <mailto:r-help@stat.math.ethz.ch> n=100; beta=1.0

I know this has been dealt with before on this list, but the previous messages lacked detail, and I haven't figured it out yet. The model is: \x_{ij} = \mu + \alpha_i + \beta_j \alpha is a random effect (subjects), and \beta is a fixed effect (condition). I have a link function: p_{ij} = .5 + .5( 1 / (1 + exp{ -x_{ij} } ) ) Which is simply a logistic transformed to be between .5 and 1.

Hello R-helpers. I've tried to recreate a parallel version of tapply() and table() using a combination of the parallel functions mclapply() and pvec() and papply(), but haven't been successful. In the end, I'm trying to get a cross tab of two vectors. I currently (can) use tapply(..., sum) and table(), and even xtabs() and ftable(), but with tens of millions of words and tens of

Henrik, the whole point and only purpose of mc* functions is to fork. That's what the multicore package was about, so if you don't want to fork, don't use mc* functions - they don't have any other purpose. I really fail to see the point - if you use mc* functions you're very explicitly asking for forking - so your argument is like saying that print() should have an option to

In pvec(list(1, 2), FUN, mc.cores=2) FUN sees integer() arguments whereas pvec(list(1, 2, 3), FUN, mc.cores=2) FUN sees list() arguments; the latter seems consistent with pvec's description. This came up in a complicated Bioconductor thread about generics and parallel evaluation https://stat.ethz.ch/pipermail/bioc-devel/2012-October/003745.html One relevant point is that a

Dear R developers, I was looking for a function analogous to base::diag() for getting and setting bands of a matrix. The closest I could find was Matrix::band(), but this was not exactly what I wanted for two reasons. Firstly, Matrix::band() returns a matrix rather than just the specified band. Secondly, Matrix::band() cannot be used for setting the values for a matrix band. Setting or