Displaying 20 results from an estimated 56 matches for "niter".
Did you mean:
inter
2011 Aug 29
3
how to start R script editor by default
Hi All,
1) Is it possible to set the options such that R opens a new script editor
every time I start the R and 2) specify the size of windows.
Thanks for the suggestion and Best regards,
Krishna
[[alternative HTML version deleted]]
2005 Jun 08
6
Random seed problem in MCMC coupling of chains
Hello!
I am performing coupling of chains in MCMC and I need the same value
of seed for two chains. I will show demo of what I want:
R code, which might show my example is:
niter <- 3
nchain <- 2
tmpSeed <- 123
for (i in 1:niter) { # iterations
for (j in 1:nchain) { # chains
set.seed(tmpSeed)
a <- runif(1)
cat("iter:", i, "chain:", j, "runif:", a, "\n")
tmpSeed <- .Random.seed
}
}
I get this:
iter:...
2007 Jun 01
2
Interaction term in lmer
...: trt (fixed) + center (random) + trt*center interaction.
Then, I want to compare these 2 models with Likelihood Ratio Test. Here are
my lmer codes that I don't feel comfortable about their correctness.
model1 <- try(lmer(cbind( yvect, nvect-yvect) ~ 1 + (1 | center),
family = binomial, niter = 25, method = "Laplace", control = list(usePQL =
FALSE) ))
model2 <- try(lmer(cbind( yvect, nvect-yvect) ~ trt*center + ( 1 | center)
,
family = binomial, niter = 25, method = "Laplace", control = list(usePQL =
FALSE) ))
(I have attached outputs below)
What I don...
2011 Jun 08
1
using stimulate(model) for parametric bootstrapping in lmer repeatabilities
...(lme4::VarCorr(model)$C, "stddev")^2 +
attr(lme4::VarCorr(model)$D, "stddev")^2 )
My question is can I use stimulate(model) to generate values that I
can then use to do parametric bootstrap analysis and generate the
confidence intervals?
Something like this:
n<-length(A)
niter<-1000
y<-matrix(nrow=n,ncol=niter*2)
for (i in 1:niter) {
y[,I(i*2-1):I(i*2)]<-simulate(model)[,1] }
rvalues<-numeric()
for (i in 1:niter) {
yboot<-cbind(y[,I(i*2-1)],y[,I(i*2)])
mboot<-lmer(y~A+B+(1|C/D)+(1|E),binomial)
rvalues[i]<- attr(lme4::VarCorr(mboot)$E, "stddev&...
2007 Jan 05
1
help for memory problem with 64-bit machines
...--------------------------------------------
>
> ##
> ## (1) For illustration of use, a small data set with very few
iterations
> ## of the algorithm, using the RM criterion.
> ##
>
> data(swiss)
> anneal(cor(swiss),2,3,nsol=4,niter=10,criterion="RM")
*** caught segfault ***
address 0x47cd37c, cause 'memory not mapped'
Traceback:
1: .Fortran("anneal", as.integer(criterio), as.integer(p),
as.double(as.vector(mat)), as.integer(kmin), as.integer(kmax),
as.double(valores), as...
2003 Dec 09
2
problem with pls(x, y, ..., ncomp = 16): Error in inherit s( x, "data.frame") : subscript out of bounds
...of components. Then why would you specify ncomp as well?
Andy
> From: ryszard.czerminski at pharma.novartis.com
>
> When I try to use ncomp parameter in pls procedure I get
> following error:
>
> > library(pls.pcr)
> > m <- pls(x, y, validation = "CV", niter = 68, ncomp = 16)
> Error in inherits(x, "data.frame") : subscript out of bounds
>
> Without ncomp parameter everything seems to work OK
>
> > dim(x)
> [1] 68 116
> > dim(y)
> [1] 68 1
> > m <- pls(x, y, validation = "CV", niter = 68)
&...
2013 Mar 26
2
Problem with nested for-loop
...(rep(1:10000,each=11))
j1data=cbind(its,j1data)
#set up a matrix full of zeros "lnbm" where prediction results are placed
#set up for loop that first loops over iteration, then species
#(total iterations=10000it/spp*11spp=110000 iterations)and then over each
tree
#(total # of trees=259)
niter=10000
nspp=11
ntrees=259
lnbm=matrix(0,10000,259)
k=numeric()
for (i in 1:ntrees)
{
for (j in 1:nspp)
{
for (m in 1:niter)
{
k=((j1data$its[m]-1)*1000)+(j1data$spp[j])
#print(k)
lnbm[m,i]=j1data$b0[k]+j1data$b1[k]*predictdata$lndbh[i]
}
}
}
Thanks
[[alternative H...
2013 Jan 18
0
problem that arises after using the new version of "BRugs"
...B <- spline.des(allKnots, x, derivs = rep(drv, length(x)),
outer.ok = TRUE)$design
Z <- B %*% LZ
attr(Z, "range.x") <- range.x
attr(Z, "intKnots") <- intKnots
return(Z)
}
BRugsMCMC<-
function (data, inits, parametersToSave, nBurnin, nIter, nThin,
modelFile)
{
if ((nBurnin < 100) | (nIter < 100))
stop("currently only working for chains longer than 100")
if ((100 * round(nBurnin/100) != nBurnin) | (100 * round(nIter/100) !=
nIter))
warning("chain lengths not multiples o...
2007 Sep 25
0
R lmer with problem of 'sd slot has negative entries'
...ary(Matrix)
library(lme4)
library(car)
library(arm)
y <- c(14, 9, 19, 12, 10, 12, 8, 11, 15, 4, 14, 13, 8, 3)
n <- c( 20, 20, 20, 20, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18)
center <- seq(1:14)
example1 <- lmer(cbind( y, n - y) ~ 1 + ( 1 | center) ,
family = binomial, niter = 50, method = "Laplace", control = list
(usePQL = FALSE))
fixef(example1)
se.fixef(example1)
example2 <- lmer(cbind( y, n - y) ~ 1 + ( 1 | center) ,
family = binomial, niter = 50, method = "Laplace", control = list
(usePQL = TRUE))
fixef(example2)
se.fixef(e...
2007 Sep 28
0
lmer giving negative, or no, estimated standard errors
...library(Matrix)
library(lme4)
library(car)
library(arm)
y <- c(14, 9, 19, 12, 10, 12, 8, 11, 15, 4, 14, 13, 8, 3)
n <- c( 20, 20, 20, 20, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18)
center <- seq(1:14)
example1 <- lmer(cbind( y, n - y) ~ 1 + ( 1 | center) ,
family = binomial, niter = 50, method = "Laplace", control = list
(usePQL = FALSE))
fixef(example1)
se.fixef(example1)
example2 <- lmer(cbind( y, n - y) ~ 1 + ( 1 | center) ,
family = binomial, niter = 50, method = "Laplace", control = list
(usePQL = TRUE))
fixef(example2)
se.fixef(examp...
2011 Oct 19
1
Sparse covariance estimation (via glasso) shrinking to a "nonzero" constant
...a) = "integer"
mode(itrace) = "integer"
mode(ipen) = "integer"
mode(is) = "integer"
mode(thr) = "double"
junk <- .Fortran("glasso", n, s, rho, ia, is, itrace, ipen,
thr, maxit = maxit, ww = ww, xx = xx, niter = integer(1),
del = double(1), ierr = integer(1), PACKAGE = "glasso")
ww = matrix(junk$ww, ncol = n)
xx = matrix(junk$xx, ncol = n)
if (junk$ierr != 0) {
stop("memory allocation error")
}
critfun = function(Sigmahati, s, rho, penalize.d...
2005 Feb 10
2
Writing output to a file in a loop
...#39;t know how to do that in any other way, to ommit this problem.
Below I enclose the code:
############################################################
library(tseries)
wig20 <- read.csv("wig20.txt", sep=";", dec=",")
m <- 2321 #upper bound of time series
niter <- 10 #length(wig20$CLOSE)- m
fcv <- 0
for (i in 1:niter){
m <- m + 1
r <- 100*diff(log(wig20$CLOSE[1:m]))
y <- r - mean(r)
fit <- garch(y, order = c(1,1))
sink("garch21.txt", append = TRUE)
summary(fit)
logLik(fit)
sink()
cv <- predict(fit...
2006 May 26
2
lme, best model without convergence
...f I get convergence depends on how the method (ML/REM) and which (and
how much) parameters will depend randomly on the cluster-variable.
How get the bist fit without convergence?
I set the parameters msVerbose and returnObject to TRUE:
lmeControl(maxIter=50000, msMaxIter=200, tolerance=1e-4, niter=50,
msTol=1e-5, nlmStepMax=500,
,msVerbose=TRUE
,returnObject=TRUE
)
However, the lme-functions does not produce verbose output, nor does it
return the best fit if lme is not converging.
It returns only an error:
Error in lme.formula(y ~ lndbh + I(lndbh^2) + lnh + I(lnh^2), random =
~lndbh...
2009 May 29
1
Problem making a package using S4 objects.
...LASS_REMORA_CONFIGURATION,
representation(number_clusters = "numeric", class_name = "character",
weighting_function="character",
scale_variance="logical", s="numeric", d="numeric", alfa="numeric", eta
= "numeric", niter="numeric", niter_changes="numeric",
perform_sum="logical", verbose="logical"),
prototype = list(number_clusters=numeric(), class_name=character(),
weighting_function=character(),
scale_variance=logical(), s=numeric(), d=numeric(), alfa=numeric(),
eta=nu...
2002 May 31
0
Convergence and singularity in glmmPQL
...> doubt5.pql<-glmmPQL(random = ~ 1 | groupid/participantid,
+ fixed = r.info.doubt ~ is.prot + is.cath + is.union
+ is.sport + is.busi,
+ data = fgdata.10statements.df,
+ na.action=na.omit,
+ niter=50,
+ family = binomial)
(the version without niter=50 just failed to converge after 10
interations; adding niter=50 gives:
iteration 1
...
iteration 26
Error in solve.default(estimates[dimE[1] - (p:1), dimE[2] - (p:1), drop =
FALSE]) :
singular matrix `a' in so...
2008 Apr 23
1
significant variables in GPLS ?
...mes="ID") #
> spex_X<-read.csv("F:/GPLS/spex_X.csv", header=TRUE, sep=";")#, row.names="ID") #
>
> test <- glpls1a(spex_X, spex_Y$A_mell,K.prov=7, br=FALSE)
> names(test)
[1] "coefficients" "convergence" "niter" "family"
[5] "link" "levs" "bias.reduction"
coefficients = regression coefficients
convergence = whether convergence is achieved
niter total = number of iterations
bias.reduction = whether Firth's procedure...
2010 Nov 10
1
Difficult doubt about choose distances randomly in a matrix with a probability of event
I would like to build a model in R to simulate the seed dispersal by one plant.
The plant produced 5 seeds and the probability of falling inside the eight closest space was 0.8 and in the next space 0.2 and in the rest space 0:
0
0
0
0
0
0
0.2
0.2
0.2
0.2
0.2
0
0.2
0.8
0.8
0.8
0.2
0
0.2
0.8
1
0.8
0.2
0
0.2
0.8
0.8
0.8
0.2
0
0.2
0.2
0.2
0.2
0.2
0
0
0
0
0
0
0
2012 Nov 15
1
confidence intervals with glmmPQL
...polynomial regression full
model with three length terms: l, l^2, and l^3 (l=length). The length terms
and intercept were the fixed effects and the random effect was a paired haul
(n=18).
m1<-glmmPQL(fixed=Proportion~1+Length+second+third,random=~1|Pair,family=binomial,data=species,verbose=T,niter=2,weight=(Experimental+Control))
For the majority of the models, I ended up with a constant model with no
length effect. The issue I am having is with the confidence intervals that
were calculated. For two models the CIs are not symmetrical around the mean
proportion from the model. The CIs for...
2007 Oct 09
2
Help with gamm errors
...ssed internally to glmmPQL (see
results of traceback())
[large data vector scrolls off screen]
6: eval(expr, envir, enclos)
5: eval(mcall)
4: glmmPQL(y ~ X - 1, random = rand, data = strip.offset(mf), family =
family,
correlation = correlation, control = control, weights = weights,
niter = niterPQL, verbose = verbosePQL)
3: eval(expr, envir, enclos)
2: eval(parse(text = paste("ret$lme<-glmmPQL(", deparse(fixed.formula),
",random=rand,data=strip.offset(mf),family=family,correlation=correlation,co
ntrol=control,",
"weights=weights,niter=niterPQL...
2003 May 30
1
Error using glmmPQL
...d/participantid,
+ fixed = r.info.doubt ~
+ realage + minority + female + education + income + scenario,
+ data = fgdata.df[coded.resource,],
+ na.action=na.omit,
+ niter=50,
+ family=binomial(link=probit))
iteration 1
iteration 2
iteration 3
iteration 4
iteration 5
iteration 6
iteration 7
iteration 8
Error in logLik.reStruct(object, conLin) :
NA/NaN/Inf in foreign function call (arg 3)
The traceback() output is very long, so...