I have this maximum liklihood estimate problem
i need to find the roots of the following:
[sum (from i=1 to n) ] ((2(x[i]-parameter)/(1+(x[i]-parameter)^2))=0
given to me is the x vector which has length 100
how would I find the roots using R?
I have 2 thoughts...... 1 is using a grid search ... eg. brute force, just
choosing a whole bunch of different values for my parameter .... such as
parameter=seq(0,100,.1) .... and this is what I have so far,
john=rep(0,length(x))
for(i in 1:length(x)) {
john[i]=((x[i]-0)/(1+(x[i]-0)^2))
}
sum(john)
then
john=rep(0,length(x))
for(i in 1:length(x)) {
john[i]=((x[i]-.1)/(1+(x[i]-.1)^2))
}
sum(john)
then
john=rep(0,length(x))
for(i in 1:length(x)) {
john[i]=((x[i]-.2)/(1+(x[i]-.2)^2))
}
sum(john)
something like this ...
theta=seq(0,100,.1)
john=rep(0,length(x))
for(i in 1:length(x)) {
john[i]=((x[i]-theta[j])/(1+(x[i]-theta[j])^2))
}
sum(john)
but something is wrong with my code because its not working. Anyone have any
ideas? (I am very new to R and statistical software in general)
The 2nd thought was to use the Newton Raphson Method, but, I dont even know
where to start with that.
Any thoughts help.
Thanks
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On Thu, 29 Nov 2007, stathelp wrote:> > I have this maximum liklihood estimate problem > > i need to find the roots of the following:Dear 'stathelp', Did you follow the Posting Guide? It would suggest that you issue something like help.search("roots") or help.search("root") which will list functions that perform root finding. Read the help pages, run the examples, then adapt one to your problem. Chuck> > [sum (from i=1 to n) ] ((2(x[i]-parameter)/(1+(x[i]-parameter)^2))=0 > > given to me is the x vector which has length 100 > > how would I find the roots using R? > > I have 2 thoughts...... 1 is using a grid search ... eg. brute force, just > choosing a whole bunch of different values for my parameter .... such as > parameter=seq(0,100,.1) .... and this is what I have so far, > > > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-0)/(1+(x[i]-0)^2)) > } > sum(john) > > then > > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-.1)/(1+(x[i]-.1)^2)) > } > sum(john) > > then > > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-.2)/(1+(x[i]-.2)^2)) > } > sum(john) > > something like this ... > > theta=seq(0,100,.1) > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-theta[j])/(1+(x[i]-theta[j])^2)) > } > sum(john) > > but something is wrong with my code because its not working. Anyone have any > ideas? (I am very new to R and statistical software in general) > > The 2nd thought was to use the Newton Raphson Method, but, I dont even know > where to start with that. > > Any thoughts help. > > Thanks > > > -- > View this message in context: http://www.nabble.com/finding-roots-%28Max-Like-Est%29-tf4901659.html#a14040895 > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >Charles C. Berry (858) 534-2098 Dept of Family/Preventive Medicine E mailto:cberry at tajo.ucsd.edu UC San Diego http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
Why exactly the same question? You were told what to do. I am new to R. I did what the previous poster said. I found it. Write your function in terms of vector operations. Avoid loops if you can. Sample input for R follows ------------------------- # par is the thing that has to be found # x are the observations f <- function(par,x) sum(2*(x-par)/(1+(x-par)^2)) # trial stuff x <- 1:10 # use uniroot to find a value for par such that f(par,x) == 0 # interval for par is obvious (lower=1 and upper=10) paropt <- uniroot(f,c(1,10),tol=1e-8,x) paropt <END OF SAMPLEINPUT> It works. Berend Hasselman On 30 Nov 2007, at 17:59, stathelp wrote:> > I have this maximum liklihood estimate problem > > i need to find the roots of the following: > > [sum (from i=1 to n) ] ((2(x[i]-parameter)/(1+(x[i]-parameter)^2))=0 > > given to me is the x vector which has length 100 > > how would I find the roots using R? > > I have 2 thoughts...... 1 is using a grid search ... eg. brute > force, just > choosing a whole bunch of different values for my parameter .... > such as > parameter=seq(0,100,.1) .... and this is what I have so far, > > > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-0)/(1+(x[i]-0)^2)) > } > sum(john) > > then > > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-.1)/(1+(x[i]-.1)^2)) > } > sum(john) > > then > > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-.2)/(1+(x[i]-.2)^2)) > } > sum(john) > > something like this ... > > theta=seq(0,100,.1) > john=rep(0,length(x)) > for(i in 1:length(x)) { > john[i]=((x[i]-theta[j])/(1+(x[i]-theta[j])^2)) > } > sum(john) > > but something is wrong with my code because its not working. Anyone > have any > ideas? (I am very new to R and statistical software in general) > > The 2nd thought was to use the Newton Raphson Method, but, I dont > even know > where to start with that. > > Any thoughts help. > > Thanks > > > -- > View this message in context: http://www.nabble.com/finding-roots-%28Max-Like-Est%29-tf4901659.html#a14040895 > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >