Displaying 5 results from an estimated 5 matches for "parameterestimation".
2005 Sep 06
2
(no subject)
my problem actually arised with fitting the data to the weibulldistribution,
where it is hard to see, if the proposed parameterestimates make sense.
data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491;
?? ?? ?? ?? ?? 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
how am I supposed to know what starting values i have to take?
i get different
2005 Sep 06
2
fitting distributions with R
...I tried to get parameterestimates for the
exponentialdistribution with R, but as the values
of the parameter are very close to 0 i get into troubles. Do you know, what i
could do in order to get estimates?How do you choose the starting values? in
my opinion it should be around 1/mean(data).
#Parameterestimation ??with mle() with the log-likelihood funktion of the ??
#exponentialdistribution
library(stats4)
ll<-function(beta)
{n<-24
x<-data2
-n*log(beta)+beta*sum(x)}
est<-mle(minuslog=ll, start=list(beta=0.1))
summary(est)
#instead of a result, i get:
Error in optim(start, f, method = m...
2005 Jul 28
1
conversion from SAS
Hi, I wonder if anybody could help me in converting
this easy SAS program into R.
(I'm still trying to do that!)
PROC IMPORT OUT= WORK.CHLA_italian
DATAFILE= "C:\Documents and
Settings\carleal\My
Documents\REBECCA\stat\sas\All&nutrients.xls"
DBMS=EXCEL2000 REPLACE;
GETNAMES=YES;
RUN;
data chla_italian;
set chla_italian;
2012 Nov 12
1
R lmer & SAS glimmix
Hi,
I am trying to fit a model with lmer in R and proc glimmix in SAS. I have
simplified my code but I am surprised to see I get different results from
the two softwares.
My R code is :
lmer(y~age_cat + (1|cat),data=fic,family=binomial(link = "logit"), NaGQ=1)
My SAS code is :
ods output Glimmix.Glimmix.ParameterEstimates=t_estimates;
proc glimmix data=tab_psi method=laplace;
2007 Apr 23
4
Estimates at each iteration of optim()?
I am trying to maximise a complicated loglikelihood function with the "optim" command. Is there some way to get to know the estiamtes at each iteration? When I put "control=list(trace=TRUE)" as an option in "optim", I just got the initial and final values of the loglikelihood, number of iterations and whether the routine has converged or not. I need to know the