search for: ntot

Hi, I make an analysis and depending of the order of the variables, the significance change, look. m1 <- glm((infec/ntot)~idade+sexo+peso,family=binomial,weights=ntot) > anova(m1,test="F") Analysis of Deviance Table Model: binomial, link: logit Response: (infec/ntot) Terms added sequentially (first to last) Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 80...

...= 1, nr = df_SMH) Y_CSMH <- matrix(0, nc = 1, nr = df_CSMH) S_GMH <- matrix(0, nc = df_GMH, nr = df_GMH) S_SMH <- matrix(0, nc = df_SMH, nr = df_SMH) S_CSMH <- matrix(0, nc = df_CSMH, nr = df_CSMH) for(k in 1:K) { V <- NULL f <- x[, , k] ntot <- sum(f) p_ip <- apply(f, 1, sum) / ntot p_pj <- apply(f, 2, sum) / ntot m <- p_ip %x% p_pj * ntot V <- ntot^2 * ((diag(p_ip) - p_ip %*% t(p_ip)) %x% (diag(p_pj) - p_pj %*% t(p_pj))) / (ntot-1) Y_GMH <- Y_GMH + A_GMH %*% (c(t(f)) - m)...

...he coordinates are the same for the same sample. This is demonstrated below using the coordinates STX2 and STY2, which are the same for a single transect. How can I properly specify this structure in Variogram() and corSpatial()? library(nlme) set.seed(1001) ntrans <- 30 npertrans <- 5 ntot <- ntrans*npertrans STX1<-runif(ntot, min=16.0921, max=16.4823) STY1<-runif(ntot, min=1.9812, max=2.3932) STX2<-rep(runif(ntrans, min=16.0921, max=16.4823), each=npertrans) STY2<-rep(runif(ntrans, min=1.9812, max=2.3932), each=npertrans) site<-rep(c(1,2,3), each=ntot/3) tran<-r...

Hi all Can anybody help me with this? I am trying to include in an automatic way the argument in arg.names in a barplot. I generate the labels I want to appear below the bars with a for loop, and they contain subscripts, so I need to use expression anch<-0.05 esp<-4 for (i in 1:dim(Ntot)[1]) { naux<-Ntot[i,] naux2<-naux[naux>0] nind<-which(naux>0) tit4<-character(0) for (j in 1:length(nind)) { tit4<-c(tit4,paste("expression(n[paste[",i,",",nind[j],"])",sep="")) } windows()...

In a package, i type a function name and got the following message: ... tmp <- .Fortran("master", x = as.double(x), y = as.double(y), sort = as.logical(sort), rw = as.double(rw), npd = as.integer(npd), ntot = as.integer(ntot), nadj = integer(tadj), madj = as.integer(madj), ind = integer(npd), tx = double(npd), ty = double(npd), ilist = integer(npd), eps = as.double(eps), delsgs = double(tdel), ndel = as.integer(ndel), delsum = double(ntdel), dirsgs =...

...); break} if (any(p > 1.0)) {cat("Some P(i) > 1.0 ","\n"); break} eps <- .Machine$double.eps^0.9 if (sum(p) > (1.0 + eps) | sum(p) < (1.0 - eps) ) {cat("Sum of P(i) should equal 1.0 ","\n"); break} # Initialize variables ntot <- n sum <- 1.0 ix <- rep(0,ncat) # Generate the observation for (icat in 1:(ncat - 1)) { prob <- p[icat]/sum ix[icat] <- rbinom(1,ntot,prob) ntot <- ntot - ix[icat] if (ntot <= 0) return(ix) sum <- s...

...) Y_CSMH <- matrix(0, nc =3D 1, nr =3D df_CSMH) S_GMH <- matrix(0, nc =3D df_GMH, nr =3D df_GMH) S_SMH <- matrix(0, nc =3D df_SMH, nr =3D df_SMH) S_CSMH <- matrix(0, nc =3D df_CSMH, nr =3D df_CSMH) for(k in 1:K) { V <- NULL f <- x[, , k] ntot <- sum(f) p_ip <- apply(f, 1, sum) / ntot p_pj <- apply(f, 2, sum) / ntot m <- p_ip %x% p_pj * ntot V <- ntot^2 * ((diag(p_ip) - p_ip %*% t(p_ip)) %x% (diag(p_pj) - p_pj %*% t(p_pj))) / (ntot-1) Y_GMH <- Y_GMH + A_GMH %*% (c(t(f)) - m)...

R helpers, I am working with the R program performing multivariate regression trees (MRT). I have a matrix with species and environmental variables saved as a CSV file (sprot_matrix.csv), I have 42 species and 8 environmental variables (SECCHI+PH+TA+PTOT+NTOT+CHLA+AREA+ MEANDEP) for 104 samples Title SpA SpB SpC SpD Varible1 Variable2 Variable3 Sample1 Sample 2 Sample 3 Sample 4 Sample 5...

...t unnecessarily complicated simulation code/demonstration: --------------- library(lme4) library(lattice) simfun <- function(reefeff,ntreat=2,nreef=12, nreefpertreat=3, t.eff=10, totvar=25,seed=NA) { if (!is.na(seed)) set.seed(seed) ntot = nreef*nreefpertreat npertreat=ntot/ntreat reef = gl(nreef,nreefpertreat) treat = gl(ntreat,npertreat) r.sd = sqrt(totvar*reefeff) e.sd = sqrt(totvar*(1-reefeff)) y.det = ifelse(treat==1,0,t.eff) r.vals = rnorm(nreef,sd=r.sd) e.vals = rnorm(ntot,sd=e.sd) y <- y.det+r.vals[as.n...

I am trying to pass an equation as an arguement to a function, which seems pretty straightforward given lazy evaluation. I constructed the following little test to make sure I sort of knew what I was doing: go <- function(X,eq) { C <<- X*2; d <<- eq} a _ rnorm(100) go(10,eq=a[.5*length(a)]+C+1) > C [1] 20 > d [1] 21.10551 > a[.5*length(a)] [1] 0.1055086 Everything

Case cohort function cch() is in survival package. In cch(), the prentice method is implemented like this: Prentice <- function(tenter, texit, cc, id, X, ntot,robust){ eps <- 0.00000001 cens <- as.numeric(cc>0) # Censorship indicators subcoh <- as.numeric(cc<2) # Subcohort indicators ## Calculate Prentice estimate ent2 <- tenter ent2[cc==2] <- texit[cc==2]-eps fit1 <- coxph(Surv(ent2,texit,cens)~X,eps=e...

...6 and 12 days after set up. So I have now following Data: Giraffe dung: wet/ dry treatment under shadow/sun condition, 3 collection times, always 5 Replikate Same for the Wildebeest dung. For the pellets I measured following variables: DW.P = dry weight pro pellet WL= water loss Ctot= total carbon Ntot=total nitrogen Now, for my statistics I used: lme(Y ~ Day*water.T*shadow.T*dung.T, random=~Day|Box/Pot) but apperently I have to fit a linear correlation for Day, so that Day is not seen as a Factor.. How have I to do that? Something Day <- corr(Day*Y)? Then I also have to calculate the regre...

Dear all, I am reading the cch function source code. But I can not understand the following codes. Please help me. What's the fitter here? fitter <- get(method) out <- fitter(tenter = tenter, texit = texit, cc = cc, id = id, X = X, ntot = nn, robust = robust) [[alternative HTML version deleted]]

...envir = .GlobalEnv) set.seed(seed) RNGstate <- structure(seed, kind = as.list(RNGkind())) on.exit(assign(".Random.seed", R.seed, envir = .GlobalEnv)) } ## get probabilities/intensities pred <- matrix(rep(predict(object,type="response"),nsim),ncol=nsim) ntot <- length(pred) if (object$family$family=="binomial") { resp <- object$model[[1]] size <- if (is.matrix(resp)) rowSums(resp) else 1 } val <- switch(object$family$family, poisson=rpois(ntot,pred), binomial=rbinom(ntot,prob=pred,size...

...le, an element of vector 'sep' is /not/ printed out after each element of the vector passed as argument '...' to cat(), "including the last" --- confer the for-loop over the elements of '...' in lines 596-617 and the print-out of the separator cat_printsep(sepr, ntot); in line 600. Once again: Is this intended? A patch fixing my problem would be easy, though might crash other much more important code; would you have any proposals? Best, Peter ------------------------------------------------------------------- Version: platform = i386-pc-mingw32 arch = i38...

...172.84 "==" 3.08 12.48 0.50 2.04 "lm.fit" 1.72 6.96 0.23 0.94 "median" (remainder omitted) nrow() has 340 total and 41 self seconds, a large portion of the total run time. There is only one call to nrow() in my code, ntot <- nrow(dati) where dati is a subset of the numeric matrix, indat. I tried replacing nrow(dati) with length(dati[,1]) The profile is then: ----------------- Rprof output, v2 ---------------- Each sample represents 0.02 seconds. Total run time: 403.699999999923 seconds. Total seconds: time sp...

...es to get the dimensions of the argument (fourier.c: 125), but gets junk instead, since the argument is not an array. 2) mvfft causes a segmentation fault or gets stuck in a loop R> mvfft(xx) Program received signal SIGSEGV, Segmentation fault. 0x80d36cb in fftmx (a=0x40617eb0, b=0x40617eb8, ntot=30, n=30, nspan=30, isn=-2, m=3, kt=0, at=0x407c8f58, ck=0x407c8f80, bt=0x407c8fa8, sk=0x407c8fd0, np=0x407c8ee4, nfac=0x8115a78) at fft.c:558 558 bt[j] = b[k1] - b[k2]; (gdb) print bt[j] Cannot access memory at address 0x407cb000. (gdb) print kspan $4 = 0 We're in a loop her...

I'm curious if anyone else is at all fed up with the current state-of-affairs of media support under *IX. As things stand it's rather a pain to add support for a new codec/framing format to an application, and it seems like were someone to step up and design a system which abstracts media support from end-user applications and supports drop-in modules for framing formats and codecs, it

...es to get the dimensions of the argument (fourier.c: 125), but gets junk instead, since the argument is not an array. 2) mvfft causes a segmentation fault or gets stuck in a loop R> mvfft(xx) Program received signal SIGSEGV, Segmentation fault. 0x80d36cb in fftmx (a=0x40617eb0, b=0x40617eb8, ntot=30, n=30, nspan=30, isn=-2, m=3, kt=0, at=0x407c8f58, ck=0x407c8f80, bt=0x407c8fa8, sk=0x407c8fd0, np=0x407c8ee4, nfac=0x8115a78) at fft.c:558 558 bt[j] = b[k1] - b[k2]; (gdb) print bt[j] Cannot access memory at address 0x407cb000. (gdb) print kspan $4 = 0 We're in a loop her...

Dear colleagues, I'm conducting a meta-analysis of studies evaluating adherence of HIV-positive drug users into AIDS treatment, therefore I'm looking for some advice and syntax suggestion for running the meta-regression using proportions, not the usual OR/RR frequently used on RCT studies. Have already searched already several handbooks, R-manuals, mailing lists, professors, but... not