Displaying 20 results from an estimated 2000 matches similar to: "Optimzing a nested function"
2005 Dec 07
1
KMO sampling adequacy and SPSS -- partial solution
Dear colleagues,
I've been searching for information on the Kaiser-Meyer-Olkin (KMO)
Measure of Sampling Adequacy (MSA). This statistic is generated in
SPSS and is often used to determine if a dataset is "appropriate" for
factor analysis -- it's true utility seems quite low, but it seems to
come up in stats classes a lot. It did in mine, and a glance through
the R-help
2019 Feb 04
2
nlminb with constraints failing on some platforms
I get the failure message. To be specific:
adcomp.git>R CMD BATCH --quiet test_nlminb.R
adcomp.git>cat test_nlminb.Rout
> f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 )
> opt <- nlminb(rep(0, 10), f, lower=-1, upper=3)
> xhat <- rep(1, 10)
> abs( opt$objective - f(xhat) ) < 1e-4? ## Must be TRUE
[1] FALSE
My system is described by:
adcomp.git>uname
2008 Jul 23
1
Calling LISP programs in R
I have written some programs in Common Lisp and I have been using SAS to pipe
those programs to my lisp compiler in batch mode by using the %xlog and
%xlst SAS commands. I wonder if there is in R a similar way to pipe commands
to LISP so that all my work would be concentrated in R even when I have to
call a LISP program? I have looked at the foreign library but this seems to
adjust data types not
2009 Sep 30
1
How to calculate KMO?
Hi All,
How do i calculate KMO for a dataset?
*Dataset:---------------------*
m1 m2 m3 m4 m5 m6 m7 m8
1 2 20 20 2 1 4 14 12
2 9 16 3 5 2 5 5 15
3 18 18 18 13 17 9 2 4
4 7 7 2 12 2 11 11 11
5 7 8 5 19 5 2 20 18
6 7 4 7 4 7 9 3 3
7 5 5 5 12 5 13 13 12
8 6 6 4 3 5 17 17 16
9 12 12 4 2 4 4 14 14
10 5 14
2012 Sep 26
2
non-differentiable evaluation points in nlminb(), follow-up of PR#15052
This is a follow-up question for PR#15052
<http://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15052>
There is another thing I would like to discuss wrt how nlminb() should
proceed with NAs. The question is: What would be a successful way to
deal with an evaluation point of the objective function where the
gradient and the hessian are not well defined?
If the gradient and the hessian both
2012 Jul 04
2
About nlminb function
Hello
I want to use the nlminb function but I have the objective function like
characters. I can summarize the problem using the first example in the
nlminb documentation.
x <- rnbinom(100, mu = 10, size = 10)
hdev <- function(par) -sum(dnbinom(x, mu = par[1], size = par[2], log =
TRUE))
nlminb(c(9, 12), objective=hdev)
With the last instructions we obtain appropriate results. If I have
2005 Dec 13
2
what does this warnings mean? and what should I do?
I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do?
> (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial"))
Generalized linear mixed model fit using PQL
2008 Dec 03
1
nlminb: names of parameter vector not passed to objective function
Dear R developers,
I tried to use nlminb instead of optim for a current problem (fitting
parameters of a differential equation model). The PORT algorithm
converged much better than any of optim's methods and the identified
parameters are plausible. However, it took me a while before spotting
the reason of a technical problem that nlminb, in contrast to optim,
does not pass names of the
2005 Nov 21
1
singular convergence with lmer function i lme4
Dear R users,
I am trying to fit a GLMM to the following dataset;
tab
a b c
1 1 0.6 199320100313
2 1 0.8 199427100412
3 1 0.8 199427202112
4 1 0.2 199428100611
5 1 1.0 199428101011
6 1 0.8 199428101111
7 0 0.8 199527103011
8 1 0.6 199527200711
9 0 0.8 199527202411
10 0 0.6 199529100412
11 1 0.2 199626201111
12 2 0.8 199627200612
13 1 0.4 199628100111
14 1 0.8
2006 Nov 01
1
Optimization and garch
Good day,
Here I was trying to write a code for Garch(1,1)
. As garch problem is more or less an optimization
problem I also tried to get the algorithm for "nlminb"
function. What I saw that if use this function
'nlminb" I can easyly get the estimate of parameters.
But any other function is not working. I tried to
write my own code for optimization using Quasi-Newton
2009 Feb 12
1
Setting optimizer in lme
I am using R 2.7.0 on a linux platform.
I am trying to reproduce a 2002 example using lme from the nlme library.
I want to change the otimizer from the default (nlminb) to optim.
Specifically, this is what I am trying to do:
R> library(nlme)
R> library(car) # for data only
R> data(Blackmoor) # from car
R> Blackmoor$log.exercise <- log(Blackmoor$exercise + 5/60, 2)
R>
2012 Oct 10
1
"optim" and "nlminb"
#optim package
estimate<-optim(init.par,Linn,hessian=TRUE, method=c("L-BFGS-B"),control =
list(trace=1,abstol=0.001),lower=c(0,0,0,0,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf),upper=c(1,1,1,1,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf))
#nlminb package
estimate<-nlminb(init.par,Linn,gr=NULL,hessian=TRUE,control =
2011 Jan 21
3
nlminb doesn't converge and produce a warning
Hi Everybody,
My problem is that nlminb doesn't converge, in minimising a logLikelihood
function, with 31*6 parameters(2 weibull parameters+29 regressors repeated 6
times).
I use nlminb like this :
res1<-nlminb(vect, V, lower=c(rep(0.01, 12), rep(0.01, 3), rep(-Inf, n-15)),
upper=c(rep(Inf, 12), rep(0.99, 3), rep(Inf, n-15)), control =
list(maxit=1000) )
and that's the result :
2004 Feb 24
2
convergence in polr
Hello splus-users, I am trying to fit a regression model for an ordered
response factor. So I am using the function polr in library(MASS). My data
is a matrix of 1665 rows and 63 columns (one of the column is the dependent
variable). The code I use is polr(as.ordered(q23p)~.,data=newdatap)
but I am getting the following warning message singularity encountered in:
nlminb.1(temp, p, liv, lv,
2011 Aug 16
2
Calibrating the risk free interest rate using nlminb
Dear R-users
I am trying to find a value for the risk free rate minimizing the difference
between a BS call value with impl. volatilities minus the market price of a
call (assuming this is just the average bid ask price)
Here is my data:
http://r.789695.n4.nabble.com/file/n3747509/S%26P_500_calls%2C_jan-jun_2010.csv
S%26P_500_calls%2C_jan-jun_2010.csv
S0 <- 1136.03
q <- 0.02145608
S0
2010 Sep 29
1
nlminb and optim
I am using both nlminb and optim to get MLEs from a likelihood function I have developed. AFAIK, the model I has not been previously used in this way and so I am struggling a bit to unit test my code since I don't have another data set to compare this kind of estimation to.
The likelihood I have is (in tex below)
\begin{equation}
\label{eqn:marginal}
L(\beta) = \prod_{s=1}^N \int
2008 Aug 08
2
Suggestion for the optimization code
Dear list,
Here's a suggestion about the different optimization code. There are
several optimization procedures in the base package (optim, optimize,
nlm, nlminb, ..). However, the output of these functions are slightly
different. For instance,
1. optim returns a list with arguments par (the estimates), value the
minimum (maxima) of the objective function, convergence (optim
2006 Apr 20
2
nlminb( ) : one compartment open PK model
All,
I have been able to successfully use the optim( ) function with
"L-BFGS-B" to find reasonable parameters for a one-compartment
open pharmacokinetic model. My loss function in this case was
squared error, and I made no assumptions about the distribution
of the plasma values. The model appeared to fit pretty well.
Out of curiosity, I decided to try to use nlminb( ) applied to
a
2015 Jul 15
1
Two bugs showing up mostly on SPARC systems
On Tue, Jul 14, 2015 at 07:52:56PM -0400, Duncan Murdoch wrote:
> On 14/07/2015 6:08 PM, Radford Neal wrote:
> > In testing pqR on Solaris SPARC systems, I have found two bugs that
> > are also present in recent R Core versions. You can see the bugs and
> > fixes at the following URLs:
> >
> >
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