Displaying 13 results from an estimated 13 matches for "llik".
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2011 Jul 01
2
Help fix last line of my optimization code
Hi
I need help figure out how to fix my code.
When I call into R
>optimize(llik,init.params=F)
I get this error message
####Error in optimize(llik, init.params = F) : element 1 is empty;
the part of the args list of 'min' being evaluated was:
(interval)####
My data and my code looks like below.
R_j R_m
0.002 0.026567296
0.01 0.003194435
. .
. .
. .
....
2007 Apr 18
3
Problems in programming a simple likelihood
...ion, I
am trying to learn to program likelihoods in R. I started with a simple
probit model but am unable to get the code to work. Any help or
suggestions are most welcome. I give my code below:
************************************
mlogl <- function(mu, y, X) {
n <- nrow(X)
zeta <- X%*%mu
llik <- 0
for (i in 1:n) {
if (y[i]==1)
llik <- llik + log(pnorm(zeta[i,], mean=0, sd=1))
else
llik <- llik + log(1-pnorm(zeta[i,], mean=0, sd=1))
}
return(-llik)
}
women <- read.table("~/R/Examples/Women13.txt", header=TRUE) # DATA
# THE DATA SET CAN BE ACCE...
2009 Jul 19
1
trouble using optim for maximalisation of 2-parameter function
...am having trouble using "optim".
I want to maximalise a function to its parameters [kind of like: univariate
maximum likelihood estimation, but i wrote the likelihood function myself
because of data issues ]
When I try to optimize a function for only one parameter there is no
problem:
llik.expo<-function(x,lam){(length(x)*log(lam))-(length(x)*log(1-exp(-1*lam*
*cons*)))-lam*sum(x)}
cons<-
data<-c(.............)
expomx<-optimize(llik.expo,c(0,100),maximum=TRUE,tol=0.0001,x=data)
expomx
To optimize to two parameters you can't use "optimize", so I tried t...
2011 Jul 03
3
Hint improve my code
Hi
I have developed the code below. I am worried that the parameters I want to
be estimated are "not being found" when I ran my code. Is there a way I can
code them so that R recognize that they should be estimated.
This is the error I am getting.
> out1=optim(llik,par=start.par)
Error in pnorm(au_j, mean = b_j * R_m, sd = sigma_j) :
object 'au_j' not found
#Yet al_j,au_j,sigma_j and b_j are just estimates that balance the
likelihood function?
llik=function(R_j,R_m)
if(R_j< 0)
{
sum[log(1/(2*pi*(sigma_j^2)))-(1/(2*(sigma_j^2))*(R_j+al_j-b_j*R_...
2011 Jul 04
3
loop in optim
...rect my loop function.
I want optim to estimates al_j; au_j; sigma_j; b_j by looking at 0 to 20,
21 to 40, 41 to 60 data points.
The final result should have 4 columns of each of the estimates AND 4 rows
of each of 0 to 20, 21 to 40, 41 to 60.
###MY code is
n=20
runs=4
out=matrix(0,nrow=runs)
llik = function(x)
{
al_j=x[1]; au_j=x[2]; sigma_j=x[3]; b_j=x[4]
sum(na.rm=T,
ifelse(a$R_j< 0, -log(1/(2*pi*(sigma_j^2)))-
(1/(2*(sigma_j^2))*(a$R_j+al_j-b_j*a$R_m))^2,
ifelse(a$R_j>0 , -log(1/(2*pi*(sigma_j^2)))-...
2005 Oct 07
2
AIC in lmer
Hello all,
Is AIC calculated incorrectly in lmer? It appears as though it uses
AIC = -2*logLik - 2*#parms, instead of -2*LogLik + 2*#parms? Below is
output from one of many models I have tried:
Generalized linear mixed model fit using PQL
Formula: cswa ~ pcov.ess1k + (1 | year)
Data: ptct50.5
Family: poisson(log link)
AIC BIC logLik deviance
224.8466 219.19 -114.4233 228.8466
2011 Jun 14
1
Using MLE Method to Estimate Regression Coefficients
...ces for the MLE procedure
# I will try the first-model first to see if I can get it to work...
x<- cbind(1,x1,x2,x3)
y<- as.vector(y)
ones<- x[,1]
# Calculate K and n for later use
K <- ncol(x)
K
[1] 4
K1 <- K + 1
n <- nrow(x)
n
[1] 81
# Define the function to be optimized
llik.regress <- function(par,X,Y) {
X <- as.matrix(x)
Y <- as.vector(y)
xbeta <- X%*%par[1:K]
Sig <- par[K1:K1]
sum(-(1/2)*log(2*pi)-(1/2)*log(Sig^2)-(1/(2*Sig^2))*(Y-xbeta)^2)
}
llik.regress
# Now let's use the above function to estimate the model.
model <- optim(c(1,1,1,1...
2011 Jul 23
1
Extend my code to run several data at once.
...current state, it means I
will have to run it 200 times manually. May you help me adjust it to
accomodate several rows of R_j and print the 200 results.
***Please do not get intimidated by the maths in the code.***
my code
######
afull=read.table("D:/hope.txt",header=T)
library(optimx)
llik = function(x)
{
al_j=x[1]; au_j=x[2]; sigma_j=x[3]; b_j=x[4]
sum(na.rm=T,
ifelse(a$R_j< 0, log(1 / ( sqrt(2*pi) * sigma_j) )-
(1/( 2*sigma_j^2 ) ) * (
(a$R_j+al_j-b_j*a$R_m)^2 ) ,
ifelse(a$R_j>0 , log(1 / ( sqrt(2*pi) * sigma_j) )-...
2003 Sep 08
1
Probit and optim in R
...<- 1.0 + 2.0 * x1 - 3.0 * x2 + rnorm(1000)
y <- latentz
y[latentz < 1] <- 0
y[latentz >=1] <- 1
#Option export of data to check estimates in STATA
#SimProbit <- data.frame(y, x1, x2)
#write.table(SimProbit, 'a:/SimProbit')
x <- cbind(1, x1 ,x2)
#Define Likelihood
llik.probit<-function(par, X, Y){
Y <- as.matrix(y)
X <- as.matrix(x)
K <- ncol(X)
b <-as.matrix(par[1:K])
phi<-pnorm(X%*%b, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE)
sum(Y*log(phi)+(1-Y)*log(1-phi))
}
grad <-function(par,X,Y){
Y <- as.matrix(y)
X <- as.matrix(...
2004 Jun 17
0
beta regression in R
...However, the
results returned by optim in R are not reasonable in terms of the value of
the log likelihood and parameter estimates.
Here is my code. Does anyone see a problem with what I'm doing here? Any
advice would be appreciated.
Thanks.
B. Dan Wood
# Define the function to be optimized
llik.beta <- function(par,X,YP) {
X <- as.matrix(x)
YP <- as.vector(y)
xbeta <- X %*% par[1:K]
p <- par[K1:K1]
sum(
-lgamma(p)
+lgamma(p+(p/xbeta-p))
-lgamma(p/xbeta-p)
+(p-1)*log(YP)
+log(1-YP)*(p/xbeta-p-1)
)
}
llik.beta
# Now use the above function to estimate the model. First, creat...
2011 Jul 06
1
Group Data indexed by n Variables
...au_j; sigma_j; b_j by looking at 0 to 20,
> 21 to 40, 41 to 60 data points.
>
> The final result should have 4 columns of each of the estimates AND 4 rows
> of each of 0 to 20, 21 to 40, 41 to 60.
>
> ###MY code is
>
> n=20
> runs=4
> out=matrix(0,nrow=runs)
>
> llik = function(x)
> {
> al_j=x[1]; au_j=x[2]; sigma_j=x[3]; b_j=x[4]
> sum(na.rm=T,
> ifelse(a$R_j< 0, -log(1/(2*pi*(sigma_j^2)))-
> (1/(2*(sigma_j^2))*(a$R_j+al_j-b_j*a$R_m))^2,
> ifelse(a$R_j>0 , -log(1/(2*pi*(sigma_j^2)))-
>...
2012 May 29
1
model frame and formula mismatch with latent class analysis poLCA
...s
ll=rep(0,Kmax) #vector of loglikelihood values
for (j in 1:Kmax){ #fits for #classes=1,2,...,Kmax
cat(j,"\n") #print current analysis number
fit[[j]]<-poLCA(f,data.int,nclass=j,nrep=20,verbose=FALSE) #20 random
starts
bic[j]<-fit[[j]]$bic #collect BICs
ll[j] <- fit[[j]]$llik #collect logliks
}
Then I get an ERROR saying " Error in model.matrix.default(formula, mframe)
:
model frame and formula mismatch in model.matrix() "
What is confusing me is that the macro runs just fine when the number of
items is restricted to 63 or less. I have checked this for...
2008 Jan 24
0
(lme4: lmer) mcmcsamp: Error in if (var(y) == 0)
...: initialize(value, ...)
4: initialize(value, ...)
3: new(if (is(object, "glmer")) "summary.glmer" else {
if (is(object, "lmer"))
"summary.lmer"
else "summary.mer"
}, object, isG = glz, methTitle = methTitle, logLik = llik, ngrps
= sapply(object at flist,
function(x) length(levels(x))), sigma = .Call(mer_sigma,
object, REML), coefs = coefs, vcov = vcov, REmat = REmat,
AICtab = AICframe)
2: summary(emnlp.m1)
1: summary(emnlp.m1)
--
David Reitter
ICCS/HCRC, Informatics, University of Edinbur...