[R] finding roots (Max Like Est)
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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[R] Help with a Loop
I am having trouble getting a loop to work for the following problem. Any
help would be much appreciated. Thanks.
I need to find the slope and intercept from the linear regression of Drug
Level on Day by Participant. There are a total of 37 Participants. I need to
store the Participant, Label, Slope, and Intercept in a new data frame.
This data is ordered by Participant number 37 total participants. A sample
of the data is given below.
Label Participant Day DrugLevel
17 0 1 15 1.84179
121 0 1 5 2.10772
147 0 1 7 3.00658
152 0 1 11 2.91729
250 0 1 10 2.75816
289 0 1 13 3.20468
321 0 1 6 2.43389
362 0 1 12 2.0
433 0 1 9 3.03167
469 0 1 8 2.97613
475 0 1 14 2.86934
70 0 2 13 0.68022
210 0 2 8 1.41767
243 0 2 11 1.28867
246 0 2 9 1.53601
247 0 2 6 1.64863
280 0 2 5 1.19795
310 0 2 12 1.24440
343 0 2 10 1.18929
413 0 2 7 1.57207
41 0 3 7 1.87884
74 0 3 8 1.82477
100 0 3 5 2.09422
133 0 3 6 1.91853
134 0 3 12 0.90422
149 0 3 11 1.38232
172 0 3 10 1.55323
216 0 3 9 1.24088
65 0 4 8 2.49412
69 0 4 5 1.79840
This is my thought process of what the loop needs to do but I cant get the
correct loop.
X1=Day[Participant=="1"]
Y1=DrugLevel[Participant=="1"]
Coeffs=function(X1,Y1)
{
lmfirst=lm(Y1~X1)
lmfirst$coefficients
}
Coeffs(X1,Y1)
# output slope and intercept here
# do same for the next participant
X2=Day[Participant=="2"]
Y2=DrugLevel[Participant=="2"]
Coeffs=function(X2,Y2)
{
lmfirst=lm(Y2~X2)
lmfirst$coefficients
}
Coeffs(X2,Y2)
# output slope and intercept here
# do same for the next participant
X3=Day[Participant=="3"]
Y3=DrugLevel[Participant=="3"]
Coeffs=function(X3,Y3)
{
lmfirst=lm(Y3~X3)
lmfirst$coefficients
}
Coeffs(X3,Y3)
# output slope and intercept here
# do same for the next participant
# etc for the rest of the participants
# any ideas?
# thanks
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