Ok, so basically I have a dataframe named data_frame
data_frame contains:
startdate
startprice
endpricethreshold1
endpricethreshold2
endpricethreshold3
all of these endpricethresholds are true/false binary vectors. They are
true or false depending on whether the endprice was above or below whatever
the endpricethreshold is.
now I want to try to use lets say the general linear model to have it try
and predict which endprice thresholds will be true or false dependent upon
startdate and startprice. So I have a formula like:
glm(endpricethreshold1 ~ ., data=data_frame[,c(1,2,3)],
family=binomial(logit));
but, for the first term endpricethreshold1(since I really have tons of
endpricethresholds and would like to make this a loop) I don't want to refer
to it by its name but instead by its column indice like this:
glm(data_frame[[3]] ~ ., data=data_frame[,c(1,2,3)],
family=binomial(logit));
However, when I do this I am getting completely different results and I have
no idea why.
If anyone could help it would be greatly appreciated.
Thanks,
Paul Fisch
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