[R] Help for i-else iwth more than one alternative

[moeby]

I try to run an if-else command line where the else argument should be the
corresponding value of the pmax command.

#####################
#opt.fc is the optimal forecast
#rmax is the vector of the maximized r squared from pmax-command of 2 data
sets containing r squares
#fc1 are the estimates of a specific forecast model (e.g. AR1)
#fc are the estimates of a specific forecast model, namely the Benchmark
(e.g. mean)

opt.fc <- as.numeric(373) #data length is 373
for (x in 1:373)
{
if (rmax[x] < 0.1)
opt.fc[x] <- fc[x] #if rmax smaller than the value 0.1 the forecast of the
benchmark should be used.
else
opt.fc[x] <- fc1[x] #else the forecast of fc model should be used.
}
So far, so easy.

How can I compute the opt.fc when I have more than one alternative forecast
model, let's say fc2 and fc3.
In Addition, I want to use the values from the forecast model where the
values of the corresponding r squared are maxed (pmax(fcr1,fcr2,fcr3...)
..... :(

any ideas?

Thank you very much in advance.





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[MacQueen, Don]

If I understand what you?re trying to do, then I believe this will do the
same as your little loop:

opt.fc <- fc
opt.fc[rmax < 0.1] <- fc1[rmax < 0.1]

(this is an example of vectorization, and it?s fundamental to how R works
and the power of R)

Then to extend it, use the same method

opt.fx[ {some expression} ] <- fc2[ {some expression} ]

But I have no idea what {some expression} should be. Perhaps it has
something to do with the maximized r squared values, but I can?t tell from
what you?ve said. In any case, the {some expression} has to result in a
logical vector of the same length as the others (373 in your example).

Hope this helps.

-Don
--
Don MacQueen

Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062

Post by moeby
I try to run an if-else command line where the else argument should be the
corresponding value of the pmax command.
#####################
#opt.fc is the optimal forecast
#rmax is the vector of the maximized r squared from pmax-command of 2 data
sets containing r squares
#fc1 are the estimates of a specific forecast model (e.g. AR1)
#fc are the estimates of a specific forecast model, namely the Benchmark
(e.g. mean)
opt.fc <- as.numeric(373) #data length is 373
for (x in 1:373)
{
if (rmax[x] < 0.1)
opt.fc[x] <- fc[x] #if rmax smaller than the value 0.1 the forecast of the
benchmark should be used.
else
opt.fc[x] <- fc1[x] #else the forecast of fc model should be used.
}
So far, so easy.
How can I compute the opt.fc when I have more than one alternative forecast
model, let's say fc2 and fc3.
In Addition, I want to use the values from the forecast model where the
values of the corresponding r squared are maxed (pmax(fcr1,fcr2,fcr3...)
..... :(
any ideas?
Thank you very much in advance.
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ve-tp4698410.html
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