Thanks for the advice everyone. All very helpful.
@Bert
Added my information to signature, thanks.
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Isaac
Research Assistant
Quantitative Finance Faculty, UTS
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Se
Dear anonymous:
1. You may be more likely to get "useful tips" on this list if you
sign with your real name. It's friendlier.
2. If you are using R "14 hours/day." get and read a good R book. The
CRAN site or Amazon lists many; choose one or more that suits your
needs.
3. Read the R Help files c
Hello, iliketurtles (?),
for whatever strange reasons you want to regress all y-columns on all
x-columns, maybe
reg <- apply( x, 2, function( xx) lm( y ~ xx))
do.call( "cbind", lapply( reg, coef))
does what you want. (To understand what the code above does, check the
documentation for lm():
You can get the ols coefficients with basic matrix operations as well (
https://files.nyu.edu/mrg217/public/ols_matrix.pdf) and by that avoid one
of the loops. I do not know how efficient this is but I have attached an
example you can paste bellow your code. Here, one x-array is used as a
right han
Hi, I'm quite new to R (1 month full time use so far). I have to run loop
regressions VERY often in my work, so I would appreciate some new
methodology that I'm not considering.
#-
y<-matrix(rnorm(100),nco
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