>why not:
>aggregate(myDataframe$TargetValue,list(SomeFactor =
myDataframe$SomeFactor),function(x) mean(x[x>quantile(x,.66)]))
Great stuff. Just what I was looking for ! Thanx a lot !!
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Hi All,
I'm looking for ways to compute aggregate statistics (with the aggregate
function) but with an option for sorting and selecting a subset of the data
frame. For example, I have would like to turn this :
aggregate(myDataframe$TargetValue,list(SomeFactor =
myDataframe$SomeFactor),mean)
in
s < 0.1
or 0.01 as 0, which would eliminate a number of variates ? Does a
decreasing order of (absolute) coefficient values amount to determining the
order of selection of variables according to LASSO ?
Thank you for your patience and for pointers.
Yves Moisan
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ctive dataset. You probably have to create
a subset first (to get M[1:5,]) and Rcmdr allows you to do that.
HTH,
Yves Moisan
_
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onal steps besides a package install of Cairo I have to
worry about ?
TIA,
Yves Moisan
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Sent from the R help mailing list archive at Nabble.com.
[[alternative
I am puzzled at the use of regression. I have a categorical variable
ClassePop33000 which factors a Population variable into 3 levels. I want to
investigate whether that categorical variable has some relation with my
dependent variable, so I go :
lm(Cout.ton ~ ClassePop33000, data=ech2)
Call:
where anova() output is
explained in more theoretical (or I should say layman-compatible) terms than
in the anova help file? How do I know which variable was selected/dropped
first, second, etc?
TIA,
Yves Moisan
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