Displaying 20 results from an estimated 44 matches for "msverbose".
2006 Mar 16
1
lme4/Matrix: Call to .Call("mer_update_y"...) and LMEoptimize gives unexpected side effect...
...uot;, x, 2, PACKAGE = "Matrix"),
fn, gr,
lower = ifelse(constr, 5e-10, -Inf),
control = list(iter.max = value$msMaxIter,
trace = as.integer(value$msVerbose)))
.Call("mer_coefGets", x, optimRes$par, 2, PACKAGE = "Matrix")
if (optimRes$convergence != 0) {
warning(paste("nlminb returned message",
optimRes$message,"\n"))...
2006 May 26
2
lme, best model without convergence
...r R-help list readers,
I am fitting mixed models with the lme function of the nlme package.
If I get convergence depends on how the method (ML/REM) and which (and
how much) parameters will depend randomly on the cluster-variable.
How get the bist fit without convergence?
I set the parameters msVerbose and returnObject to TRUE:
lmeControl(maxIter=50000, msMaxIter=200, tolerance=1e-4, niter=50,
msTol=1e-5, nlmStepMax=500,
,msVerbose=TRUE
,returnObject=TRUE
)
However, the lme-functions does not produce verbose output, nor does it
return the best fit if lme is not converging.
It returns only...
2004 Nov 30
1
lme in R-2.0.0: Problem with lmeControl
Hello!
One note/question hier about specification of control-parameters in the
lme(...,control=list(...)) function call:
i tried to specify tne number of iteration needed via
lme(....,control=list(maxIter=..., niterEM=...,msVerbose=TRUE))
but every time i change the defualt values maxIter (e.g. maxIter=1,
niterEM=0) on ones specified by me, the call returns all the iterations
needed until it's converged.
and this is exactly the problem i will to get round. ( e.g. in
example on p.81 of Pinheiro/Bates,2000:
fm1Rail...
2012 Apr 18
1
Add covariate in nlme?
...t a nonlinear mixed model that includes
Process as a fixed covariate:
nlme.model001epr <- nlme(result ~ A0 * exp(- ( exp(A1) * exp(-Ea /
(0.0083144*TEMP.K)) * exp(eps)) * time),
data = Parameterg,
fixed=list(A0+Ea~1,A1~Process),
random=eps~1,
start=c(93, 92, 34.5,37),
control=list(msVerbose=TRUE, maxIter = 200),
verbose=TRUE, method="REML",
na.action=na.pass)
this fit give the following error:
Error in MEEM(object, conLin, control$niterEM) :
Singularity in backsolve at level 0, block 1
HOWEVER, in SAS the same model with covariate is WORKING!
When I'm changing t...
2006 Aug 04
1
gnlsControl
...arameters in
gnlsControl to change to get convergence.
Cheers
Dan Coleman
Genentech Inc.
> gnlsControl
function (maxIter = 50, nlsMaxIter = 7, msMaxIter = 50, minScale = 0.001,
tolerance = 1e-06, nlsTol = 0.001, msTol = 1e-07, msScale = lmeScale,
returnObject = FALSE, msVerbose = FALSE, apVar = TRUE, .relStep =
(.Machine$double.eps)^(1/3),
nlmStepMax = 100, opt = c("nlminb", "optim"), optimMethod = "BFGS",
minAbsParApVar = 0.05)
{
list(maxIter = maxIter, nlsMaxIter = nlsMaxIter, msMaxIter = msMaxIter,
minScale = m...
2007 Dec 05
0
lme output
Dear all,
I noticed the following in the call of lme using msVerbose.
fm1 <- lme(distance ~ age, data = Orthodont, control = lmeControl(msVerbose=T))
9 318.073: -0.567886 0.152479 1.98021
10 318.073: -0.567191 0.152472 1.98009
11 318.073: -0.567208 0.152473 1.98010
fm2 <- lme(distance ~ age, random =~age, data = Orthodo...
2006 Jul 23
1
How to pass eval.max from lme() to nlminb?
Dear R community,
I'm fitting a complex mixed-effects model that requires numerous
iterations and function evaluations. I note that nlminb accepts a
list of control parameters, including eval.max. Is there a way to
change the default eval.max value for nlminb when it is being called
from lme?
Thanks for any thoughts,
Andrew
--
Andrew Robinson
Department of Mathematics and Statistics
2010 Apr 14
1
creating a new corClass for lme()
...SPT <- function(object,...) {
Dim(object[["time"]],...)
}
############ END ###############
When I run this model on:
mymodel <- lme(fixed = e ~ a,random= ~ 1 |
g,data=df,correlation=corSPT(corCAR1(.2,form = ~ t | g),corExp(c(1,.5),form=
~ x + y | g, nugget=TRUE)),control=list(msVerbose=TRUE))
I get sensible results. However if I change the way the temporal data is
modeled:
mymodel <- lme(fixed = e ~ a,random= ~ 1 |
g,data=df,correlation=corSPT(corExp(.2,form = ~ t | g),corExp(c(1,.5),form=
~ x + y | g, nugget=TRUE)),control=list(msVerbose=TRUE))
I get a C runtime error. I h...
2006 Jan 31
1
lme in R (WinXP) vs. Splus (HP UNIX)
...y
different. Here is my R code and output, with some columns
and rows deleted for space considerations:
FOO.lme1 <- lme(fixed = Y ~ X1*X2,
random = ~ X2 | X3, data = FOO,
method = "REML",
control = list(maxIter = 200, msMaxIter = 200,
tolerance = 1e-8, niterEM = 200,
msTol = 1e-8, msVerbose = TRUE,
optimMethod = "Nelder-Mead"))
0 203.991: 0.924323 -0.0884338 0.493897
1 203.991: 0.924323 -0.0884338 0.493897
> summary(FOO.lme1)
Linear mixed-effects model fit by REML
Data: FOO
AIC BIC logLik
357.484 373.6868 -170.7420
Random effects:
Form...
2006 Sep 11
3
Extracting overdispersion estimates from lmer amd glm objects
.... I am imaging that in theory it should be possible with some call to attr(), but i have so far had no success.
An example model output would be:
> modeltest<-lmer(Coleodactylus_amazonicus_N~USD + (1|site),data=SFArray,family=poisson,method="Laplace",control=list(usePQL=FALSE, msVerbose=TRUE))
> summary(modeltest)
------------
Generalized linear mixed model fit using Laplace
Formula: Coleodactylus_amazonicus_N ~ USD + (1 | site)
Data: SFArray
Family: poisson(log link)
AIC BIC logLik deviance
75.94996 81.68603 -34.97498 69.94996
Random effects:
Groups Na...
2006 Jun 29
1
lmer - Is this reasonable output?
...ed siteid. I'm estimating a logistic regression model
with random intercept and another version with random intercept and
random slope for one of the independent variables.
fit.1 <- lmer(glaucoma~(1|siteid)+x1
+x2,family=binomial,data=set1,method="ML",
control=list(usePQL=FALSE,msVerbose=TRUE))
Generalized linear mixed model fit using PQL
Formula: glaucoma ~ (1 | siteid) + x1 + x2
Data: set1
Family: binomial(logit link)
AIC BIC logLik deviance
236.7448 249.4944 -114.3724 228.7448
Random effects:
Groups Name Variance Std.Dev.
siteid (Intercept) 0....
2006 Apr 28
1
variance using lmer
...ance of the binomial probit model.
I have fitted the following model :
> lmer1<-lmer(mp ~ l + op + l*op+ us_lev + bw_lev +(1|tatu) ,
+ family = binomial(link="probit"),
+ method = 'Laplace',
+ data = matings,
+ msVerbose= True)
> summary(lmer1)
Generalized linear mixed model fit using Laplace
Formula: mp ~ l + op + l * op + us_lev + bw_lev + (1 | tatu)
Data: matings
Family: binomial(probit link)
AIC BIC logLik deviance
1455.121 1556.387 -706.5605 1413.121
Random effects:
Groups...
2006 Jan 25
1
About lmer output
Dear R users:
I am using lmer fo fit binomial data with a probit link function:
> fer_lmer_PQL<-lmer(fer ~ gae + ctipo + (1|perm) -1,
+ family = binomial(link="probit"),
+ method = 'PQL',
+ data = FERTILIDAD,
+ msVerbose= True)
The output look like this:
> fer_lmer_PQL
Generalized linear mixed model fit using PQL
Formula: fer ~ gae + ctipo + (1 | perm) - 1
Data: FERTILIDAD
Family: binomial(probit link)
AIC BIC logLik deviance
2728.086 2918.104 -1332.043 2664.086
Random effects:
Groups...
2011 May 29
1
Setting max. iterations for lmer
...ntrol a list of control parameters. See below for details.
control
a named list of control parameters for the estimation algorithm, specifying
only the ones to be changed from their default values. Hence defaults to an
empty list.
Possible control options and their default values are:
msVerbose:
a logical value passed as the trace argument to nlminb (see documentation
on that function). Default is getOption("verbose").
maxIter:
a positive integer passed as the maxIter argument to nlminb (see
documentation on that function). Default is 300.
maxFN:
a positive integer specifying...
2012 Feb 05
1
Covariate model in nlme
...armacokinetic model. The base model is
parameterized in terms of CL, V1, V2 and Q.
basemodel<-nlme(Conc ~TwoCompModel(CL,Q,V1,V2,Time,ID),
data = data2, fixed=list(CL+Q+V1+V2~1),
random = pdDiag(CL+V1+V2~1),
start=c(CL=log(20),Q=log(252),V1=log(24.9),V2=log(120)),
control=list(returnObject=TRUE,msVerbose=TRUE,
msMaxIter=20,pnlsMaxIter=20,pnlsTol=1),
verbose=TRUE).
Now, I want to include covariates (age and weight) in the base model. The
relationships between CL and covariate is linear and given as the following
equation.
CL=TVCL+a*wt-b*age, where TVCL is mean clearance, a and b are coefficients
o...
2001 Dec 05
1
how to obtain EM-estimates of cov(b) and var(e) from lme
...+ b1 x + r0 + r1 x + e
where b0 and b1 are fixed parameters, r0 and r1 are random,
e ~ N(0,s2 I) and R' = [r0, r1] ~ N(0,T).
I try to obtain the EM-estimates of s2 and the elements of T by
lme(y~x,data=mydata,random= list(group=~x),
control=lmeControl(maxIter = 0, niterEM=100,msVerbose = TRUE))
Does this statement do the job?
Thank you very much.
Cheers!
Han-Lin Lai, Ph.D
Han-Lin.Lai at noaa.gov
508-495-2312
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r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "i...
2003 Apr 19
1
nls, gnls, starting values, and covariance matrix
...250
However, I'd like to be able to fit the model using gnls. The format is a
little different, but I get an error when I use the following syntax:
gnls(Y~log(exp(a0-a1*X)+exp(b0-b1*X)),params=a0+a1+b0+b1~K,start=list(rep(c
(6.02,0.2,4.5,0.001),16)),data=data.frame(Y=y,X=x,K=k),control=list
(msVerbose=TRUE,apVar=FALSE,returnObject=TRUE))
Error in gnls(Y ~ log(exp(a0 - a1 * X) + exp(b0 - b1 * X)), params = a0 + :
Approx. covariance matrix for parameter estimates not of full rank
I assume that I'm getting the format of my starting values wrong. Any
suggestions would be greatly app...
2005 Aug 18
1
Error messages using LMER
Dear All,
After playing with lmer for couple of days, I have to say that I am
amazed! I've been using quite some multilevel/mixed modeling packages,
lme4 is a strong candidate for the overall winner, especially for
multilevel generzlized linear models.
Now go back to my two-level poisson model with cross-classified model.
I've been testing various different model specificatios for the
2005 Dec 29
1
'last.warning' problem at startup; package Matrix (PR#8453)
...ace' for 'Matrix'
The only object in my .RData is last.warning, thus:
> last.warning
$"optim or nlminb returned message false convergence (8)"
"LMEoptimize<-"(`*tmp*`, value = list(maxIter = 200, tolerance =
1.49011611938477e-08,
msMaxIter = 200, msVerbose = 0, niterEM = 15, EMverbose = FALSE,
PQLmaxIt = 30, analyticGradient = TRUE, analyticHessian = FALSE))
This was generated by a call, in a previous session,to lmer()
There may be a problem with the package Matrix, but it seems a bit
extreme that this prevents restoration of the session.
Joh...
2002 Mar 31
1
lme degrees of freedoms: SAS and R
...or can somebody explain which is correct and why?
Thanks a lot!
Kaiya Liu
-------------------------------------
Here are the codes:
For R:
> formula (SIMS)
Gain ~ Pretot | Class
> data(SIMS)
> fm1SIMS <- lme(Gain ~ Pretot, data = SIMS, random = ~ Pretot | Class,
control = list(msVerbose = TRUE))
> summary (fm1SIMS)
_________________________________
For SAS:
proc mixed data=sims;
class class;
model gain = pretot / solution;
random intercept pretot / subject=class type=un;
run;
Most of the results are comparable except the degrees of freedoms for the
fixed effects...