search for: pvec

Given a vector : pvec=(p1,p2,.... p J) with sum(pvec)=1, all the elements are non-negative, that is, they are probabilities a matrix A ( N* J ), with the elements alpha(ij) are 0 or 1 I want to MAXIMIZE THE RESULT RESULT= product( i=1, to N [ sum ( alpha(ij)* pj , j =1,to J ) ] ) th...

...ture(c(3L,4L,3L,2L,1L), .Names = c("1", "2", "3", "4", > "5")) > > RN<-function(y=desman.y,J=5,nsites=39,Nmax=100){ + #### + lik<-function(parms){ + r<-expit(parms[1]) + lambda<-exp(parms[2]) + pvec<-1-(1-r)^(0:Nmax) + gN<-dpois(0:Nmax,lambda) + gN<-gN/sum(gN) + lik<-rep(NA,nsites) + for(i in 1:nsites){ + lik[i]<-sum(dbinom(y[i],J,pvec)*gN) + } + -1*sum(log(lik)) + } + #### + + tmp<-nlm(lik,c(0,0),...

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.et...

...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, npost, tol=0.01, verbose=FALSE) But I don't get the right Bayesian CI. What am I doing wrong? Thanks! Tina -- View this message in context: http://r.789695.n4.nabble.com/Bayesian-Credible-Intervals-for-a-Proporti...

...put_page is aware of > LRU list so if it releases last refcount of the page, it removes > the page from LRU list. However, It makes unnecessary operations > (e.g., lru_cache_add, pagevec and flags operations. Yeah, and compaction (perhaps also other migration users) has to drain the lru pvec... Getting rid of this stuff is worth even by itself. > It would be > not significant but no worth to do) and harder to support new > non-lru page migration because put_page isn't aware of non-lru > page's data structure. > > To solve the problem, we can add new hook in p...

...put_page is aware of > LRU list so if it releases last refcount of the page, it removes > the page from LRU list. However, It makes unnecessary operations > (e.g., lru_cache_add, pagevec and flags operations. Yeah, and compaction (perhaps also other migration users) has to drain the lru pvec... Getting rid of this stuff is worth even by itself. > It would be > not significant but no worth to do) and harder to support new > non-lru page migration because put_page isn't aware of non-lru > page's data structure. > > To solve the problem, we can add new hook in p...

...environment variable make sense? I've prototyped a working patch that works like: > options(fork.allowed = FALSE) > unlist(parallel::mclapply(1:2, FUN = function(x) Sys.getpid())) [1] 14058 14058 > parallel::mcmapply(1:2, FUN = function(x) Sys.getpid()) [1] 14058 14058 > parallel::pvec(1:2, FUN = function(x) Sys.getpid() + x/10) [1] 14058.1 14058.2 > f <- parallel::mcparallel(Sys.getpid()) Error in allowFork(assert = TRUE) : Forked processing is not allowed per option ?fork.allowed? or environment variable ?R_FORK_ALLOWED? > cl <- parallel::makeForkCluster(1L) Error...

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", "PR8", "PR9", "PR10") fun11 <- function(x){ smpool <- c(1,2,3,3) x <- sample(smpool, 10, replace= TRUE) } newd <- sapply...

I am using the package of Icens but for the function Bisect I do not know what ndir is it just says the direction of pvec, but what kind of values should I use ? thanks for reply pls give me an example.. Bisect(tA, pvec, ndir, Meps, tolbis=1e-07) Arguments: tA: The transpose of the clique matrix. pvec: The current estimate of the probability vector. ndir: The direction to explore. Mep...

...t; 0) && (conf.level < 1))) stop("conf.level must be a single number between 0 and 1") DNAME <- paste(deparse(substitute(x)), "and", deparse(substitute(n))) PVAL <- switch(alternative, less = pbinom(x, n, p), greater = 1 - pbinom(x - 1, n, p), { pvec <- pbinom(0:n, n, p) if(x/n < p) { pb <- pbinom(x, n, p) p2 <- max((1 - pvec) [pb - (1 - pvec) >= - eps * pb], 0) min(1, pb + p2) } else { pb <- (1 - pbinom(x - 1, n, p)) p2 <- max(pvec[pb - pvec >= - eps * pb], 0) min(1, pb + p2) }...

Hello List does anyone have an R function for the Lambert W function? I need complex arguments. [the Lamert W function W(z) satisfies W(z)*exp(W(z)) = z but I could'nt even figure out how to use uniroot() for complex z] -- Robin Hankin Uncertainty Analyst Southampton Oceanography Centre SO14 3ZH tel +44(0)23-8059-7743 initialDOTsurname at soc.soton.ac.uk (edit in obvious way; spam

...rking patch that >> works like: >>> options(fork.allowed = FALSE) >>> unlist(parallel::mclapply(1:2, FUN = function(x) Sys.getpid())) >> [1] 14058 14058 >>> parallel::mcmapply(1:2, FUN = function(x) Sys.getpid()) >> [1] 14058 14058 >>> parallel::pvec(1:2, FUN = function(x) Sys.getpid() + x/10) >> [1] 14058.1 14058.2 >>> f <- parallel::mcparallel(Sys.getpid()) >> Error in allowFork(assert = TRUE) : >> Forked processing is not allowed per option ?fork.allowed? or >> environment variable ?R_FORK_ALLOWED? >&g...

...e(res0 <- startsWith(grams, "900001")) user system elapsed 0.658 0.012 0.669 which returns the same result as grepl > identical(res0, res1 <- grepl("^900001", grams)) [1] TRUE One can also parallelize the already vectorized grepl function with parallel::pvec, with some opportunity for gain (compared to grepl) on non-Windows > system.time(res2 <- pvec(seq_along(grams), function(i) grepl("^900001", grams[i]), mc.cores=8)) user system elapsed 24.996 1.709 3.974 > identical(res0, res2) [[1]] TRUE I think anything else wo...

Hello I'm plotting some data using matplot with a logarithmic scale on the y-axis. This is the call to matplot I'm using: matplot(turns, distances, type = "l", log = "y", lty = "solid", ylab = "", xlab = "Time steps", col = c("black")) The values for the 'distances' vector are always between 0 and 1. The

...>LRU list so if it releases last refcount of the page, it removes > >the page from LRU list. However, It makes unnecessary operations > >(e.g., lru_cache_add, pagevec and flags operations. > > Yeah, and compaction (perhaps also other migration users) has to > drain the lru pvec... Getting rid of this stuff is worth even by > itself. Good note. Although we cannot remove lru pvec draining completely, at least, this patch removes a case which should drain pvec for returning freed page to buddy. Thanks for the notice. > > >It would be > >not significant...

Dear R users: Sorry for this simple question: I am writing a function where I would need to pickup p values and make -log10 of it. The p values are from an anova output and sometime it can yield me 0. -log10 (0) [1] Inf I can not replace Inf with 0, which not case here. This is restricting me to go further in the function and out me the error. You help is highly appreciated. Thanks; --

...'ve prototyped a working patch that > works like: > >> options(fork.allowed = FALSE) >> unlist(parallel::mclapply(1:2, FUN = function(x) Sys.getpid())) > [1] 14058 14058 >> parallel::mcmapply(1:2, FUN = function(x) Sys.getpid()) > [1] 14058 14058 >> parallel::pvec(1:2, FUN = function(x) Sys.getpid() + x/10) > [1] 14058.1 14058.2 >> f <- parallel::mcparallel(Sys.getpid()) > Error in allowFork(assert = TRUE) : > Forked processing is not allowed per option ?fork.allowed? or > environment variable ?R_FORK_ALLOWED? >> cl <- parall...

...t;>> options(fork.allowed = FALSE) >>>>> unlist(parallel::mclapply(1:2, FUN = function(x) Sys.getpid())) >>>> [1] 14058 14058 >>>>> parallel::mcmapply(1:2, FUN = function(x) Sys.getpid()) >>>> [1] 14058 14058 >>>>> parallel::pvec(1:2, FUN = function(x) Sys.getpid() + x/10) >>>> [1] 14058.1 14058.2 >>>>> f <- parallel::mcparallel(Sys.getpid()) >>>> Error in allowFork(assert = TRUE) : >>>> Forked processing is not allowed per option ?fork.allowed? or >>>> envir...

On Mon, 15 Apr 2019 at 08:44, Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > On 4/13/19 12:05 PM, I?aki Ucar wrote: > > On Sat, 13 Apr 2019 at 03:51, Kevin Ushey <kevinushey at gmail.com> wrote: > >> I think it's worth saying that mclapply() works as documented > > Mostly, yes. But it says nothing about fork's copy-on-write and memory >

...>>>>>>> unlist(parallel::mclapply(1:2, FUN = function(x) Sys.getpid())) >>>>>> [1] 14058 14058 >>>>>>> parallel::mcmapply(1:2, FUN = function(x) Sys.getpid()) >>>>>> [1] 14058 14058 >>>>>>> parallel::pvec(1:2, FUN = function(x) Sys.getpid() + x/10) >>>>>> [1] 14058.1 14058.2 >>>>>>> f <- parallel::mcparallel(Sys.getpid()) >>>>>> Error in allowFork(assert = TRUE) : >>>>>> Forked processing is not allowed per option ?fork.al...