Hi,
I usually use optimize function for ML Estimation. Now I´ve got a data frame
with many sets, but I can´t save estimates each time I run the code for each
data set (I´m using a for loop with my loglikelihood function and works ok but
when I apply another for loop to:
optimize(my.loglikelihood.function[i], int=c(0.0001,10))
it doesn´t work;
alternatively, using optimize inside the for loop (like in the example below),
it returns always the same value, which is not expected:
data<-matrix(c(1,1,1, 2,2,2, 3,3,3, 4,4,4), nrow=3, ncol=4)
c<-dim(data)[2]
results<-vector(length=c)
for (i in 1:c){
f<-function(x){
x^2+x*sum(data[,i])
}
results[i]<-optimize(f,int=c(0.0001,10))[1] #minimum
}
#results
Can someone please indicate me if there´s a different function/ way to do so?
(with no need of initial parameter values)
Thanks! Sandra
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