search for: startval

...k* my likelihood is written properly and I *think* I am handling flow control issues in a relatively decent way. I may be misinterpreting optim or nlminb reports. In any event, should anyone take the time to review this and offers pointers I would be grateful. Harold fit <- function(data, Q, startVal = NULL, ...){ if(!is.null(startVal) && length(startVal) != ncol(data) ){ stop("Length of argument startVal not equal to the number of parameters estimated") } if(!is.null(startVal)){...

...tasets methods base other attached packages: [1] ltm_0.9-2 polycor_0.7-7 sfsmisc_1.0-9 mvtnorm_0.9-8 msm_0.9.4 MASS_7.3-3 MiscPsycho_1.5 [8] statmod_1.4.1 loaded via a namespace (and not attached): [1] splines_2.10.0 survival_2.35-7 tools_2.10.0 mml2 <- function(data, Q, startVal = NULL, gr = TRUE, ...){ if(!is.null(startVal) && length(startVal) != ncol(data) ){ stop("Length of argument startVal not equal to the number of parameters estimated") } if(!is.null(startVal)){...

...189981, 2.098671, 2.122207, 2.012621, 1.963610, 1.884184, 1.955160, 1.801175, 1.829686, 1.773260, 1.588768, 1.563774, 1.559192) tpoints <- c(0,0,0,2,2,2,4,4,4,6,6,6,8,8,8,12,12,12,14,14,14,16,16,16,18,18,18,20,20,20,24,24,24) shift=mean(gene_expression) # y-axis (expression) shift # Perfect fit startvals <- list(phase=pi, amp=0.5) sine_nls <- nls(gene_expression ~ sin(tpoints * afreq + phase) * amp + shift, start=startvals, algorithm="port", lower=lowervals, upper=uppervals) # Convergence failure startvals <- list(phase=0, amp=0.5) sine_nls <- nls(gene_expression ~ sin(tpoin...

...y inaccurate. I am sending my programme. It would be of great help if someone can point me, where I am going wrong. ############################################################ library(MASS) Sigma <- matrix(c(4,2.8,2.8,4),2,2) y<-mvrnorm(n=1000, rep(0, 2), Sigma) mlebinorm<- function(startval, y)# startval = Initial Values to be passed , y= data { startval<-as.numeric(startval) oneside=matrix(c(0,0,0,0,-1,0,0,0,0,1),5,2) otherside = c(-0.9999999,-0.999999) n<- ncol(y) nf<- function(x) { mu1<-x[1] mu2<-x[2] sig1<-x[3] sig2<-x[4] rho<-x[5] nf<-...

...I solve the following simple example? x^2 - y^2 = 6 x ? y = 3 I heard about nlsystemfit, but I don?t know how to run it exactly. I have tried the following code, but it doesn?t really work: f1 <-y~ x[1]^2-x[2]^2-6 f2 <-z~ x[1]-x[2]-3 f <- list(f1=0,f2=0) nlsystemfit("OLS",f,startvals=c(0,0)) Thank You in advance for your help. Evgeniq Petrova

...= x[5] TH = 45 theta = x[6] qe = qeo + dqe*T theta = phi = (TH-To)/(To-TL) Fm = Fmo*((T-TL)*(TH-T)^ phi) / ((To-TL)*(TH-To)^ phi) Aest = (qe*PAR + Fm - ((qe*PAR + Fm)^2 - 4*theta*qe*PAR*Fm)^0.5)/(2.*theta) result = sum((Aest-A)^2 ) } # ------------ Define parameter starting values and limits startval = c(0.05,-0.01,20, -5,15,0.5) lowval = c(0.01,-0.05, 5,-15, 7,0.1) uppval = c(0.2, 0.02,50, 0,25,0.99) # ------------ Fit using entire data set R3 <- nlminb(startval, fnonRecHypT, control=list(trace=1), lower=lowval, upper = uppval) # ------------ estimate fit parameter standard err...

...VAddRecExpr>(Accum) && cast<SCEVAddRecExpr>(Accum)->getLoop() == L)) { SCEV::NoWrapFlags Flags = SCEV::FlagAnyWrap; @@ -3071,11 +3091,40 @@ const SCEV *ScalarEvolution::createNodeForPHI(PHINode *PN) { } const SCEV *StartVal = getSCEV(StartValueV); - const SCEV *PHISCEV = getAddRecExpr(StartVal, Accum, L, Flags); + const SCEV *PHISCEV; + if (zext && trunc) { + // We have an induction variable 'iv' of the form: + // iv=add(zext(trunc(...

Hi everyone, I am new to R and keep getting the message Error in as.vector(x, mode) while trying to run nlsystemfit. Below is my exact code. The data is in Stata format because I only recently swapped to R and am trying to compare results from Stata to make sure I know what is going on. I have searched google and read sever R-help articles with this error. They all say the problem is to do

...p(thetareal, c(FALSE, o[ss, ])) 8: emfred(x, thetaold, indx$o, indx$m, indx$ivector, indx$icap, indx$AMr1, indx$AMr2, AM1stln = AM1stln, returntype = "theta", priors = priors, empri = empri, collect = collect) 9: emarch(x.stacked$x, p2s = p2s, thetaold = NULL, tolerance = tolerance, startvals = startvals, x.stacked$priors, empri = empri, frontend = frontend, collect = collect, autopri = prepped$autopri, emburn = emburn) 10: amelia.default(datM, m = 5, idvars = "group") 11: amelia(datM, m = 5, idvars = "group") Warning: stack imbalance in '<-', 108 the...

Dear R-users I'm running a maximum likelihood procedure using the spg package. I'd like to save some output produced in each iteration to a file, but if I put the capture.output() within the function I get the following message; Error in spg(par = startval, fn = loglik, gr = NULL, method = 3, lower = lo, : Failure in initial function evaluation!Error in -fn(par, ...) : invalid argument to unary operator I have considered putting the capture.output() after the function, but there are some issues with R stalling on me so I'd like that the outpu...

I am trying to it a particular nonlinear model common in Soil Science to moisture release data from soil. I have written the function as shown below according to the logist example in Ch8 of Pinheiro & Bates. I am getting the following error (R version 2.1.1) *Error in qr(attr(rhs, "gradient")) : NA/NaN/Inf in foreign function call (arg 1)* Below is the function and data. /#

...2 1 1 2 1 1 1 2 ... $ os : num 0 1 0 0 1 1 1 0 0 1 ... $ css : num 0 1 0 0 1 1 1 0 0 1 ... $ rfs : num 0 1 1 0 1 1 1 0 0 1 ... $ comp : num 0 1 1 0 1 1 1 0 0 1 ... > set.seed(200) > M <- 50 # Number of imputations > am.imp <- amelia(utt.mi, m=M, p2s=1, startvals=1, write.out=F, + idvars=c('os','css','rfs','comp'), + noms=c('gender','symptoms','site','multifoc','ctnm','prebca','precystec' , + 'smk','surgery','ptnm.t','nodes','grade...

...cause execution to transfer back ; to this context as if from a return from llvm.swapcontext. The linked ; context pointer stored in %pThisCtx is not modified. declare void llvm.swapcontext({}* %pThisCtx, {}* %pNewCtx) A simple example using these intrinsics: define void @co1({}* %thisCtx, i32 %startVal) nounwind { entry: %prevCtx = call {}* @llvm.getlinkcontext(%thisCtx) ; Now call print messages. After each print message, temporarily yield ; control back to the previous context. call void @printCo1FirstMessage(i32 %startVal) call void @llvm.swapcontext({}* %thisCtx, {}* %prevCtx) c...

...e operation to test to see if the column is all zeros and tally up a character vector with the names of the columns to obtain the terms in equation i eqn.terms <- vector() for( v in 1:length( est$estimate ) ) { j <- attr( eval( deriv( as.formula( eqns[[i]] ), names( startvals ) ) ), "gradient" ) if( qr( j[,v] )$rank > 0 ) { eqn.terms <- rbind( eqn.terms, name <- names( est$estimate )[v] ) } } derivs[[i]] <- deriv( as.formula( eqns[[i]] ), eqn.terms, hessian=T )...

...etach(package: Hmisc) --------------- After examining the missing data patterns, impute 10 datasets using the amelia function from the Amelia package. Check the densities of the continuous variables to make sure they make sense. --------------- library(Amelia) am.imp <- amelia(d, m=10, p2s=1, startvals=1, write.out=F, noms=c('status','sex','hepmeg','trt')) compare.density(data=d, output=am.imp, var='trig') compare.density(data=d, output=am.imp, var='platelet') --------------- Since everything looks ok, fit Cox models to each of the 10 imputed dat...

Kenneth Uildriks <kennethuil at gmail.com> wrote: > As I see it, the context switching mechanism itself needs to know > where to point the stack register when switching.  The C routines take > an initial stack pointer when creating the context, and keep track of > it from there.  If we don't actually need to interoperate with > contexts created from the C routines, we have

+CC llvm-dev On Tue, May 8, 2018 at 2:34 AM, Gal Zohar <Gal.Zohar at ceva-dsp.com> wrote: > I noticed that SCEV, when trying to perform strength reduction, doesn’t use > the ability to prove an induction variable does not signed/unsigned wrap due > to infinite loops. > > Is there an easy way to use the isAddRecNeverPoison function when > determining if strength reduction

Hi, I'm trying to fit some data using a logistic function defined as y ~ a * (1+m*exp(-x/tau)) / (1+n*exp(-x/tau) My data is below: x <- 1:100 y <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,1,1,1,2,2,2,2,2,3,4,4,4,5, 5,5,5,6,6,6,6,6,8,8,9,9,10,13,14,16,19,21, 24,28,33,40,42,44,50,54,69,70,93,96,110,127,127,141,157,169,