If I create an aggregation like this:
aggregate(lastYear[,8:10],list(Stadium=lastYear$STAD),mean)
I'll get a new data frame, which I can order if I assign it like this:
newFrame <- aggregate(lastYear[,8:10],list(Stadium=lastYear$STAD),mean)
newFrame[order(newFrame$TEMP),]
But.. if I just want t
I have two distributions. Both are left skewed. Is there a good
statistical approach to determining if the skew of distribution 1 is
statistically similar to the skew of distribution 2?
Thanks,
bp
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R-hel
I'm trying to identify patterns among various "paths" like the following:
http://i.imgur.com/bQPI3.png
If I plot these, I can observe intuitively two different patterns: a front
loaded (1 and 3) and a backloaded (2,4) progress path:
http://i.imgur.com/L5qwZ.png
I have thousands of observations
Using ordered probit model, I get errors from dwt and bptest.
dwt:
Error in durbinWatsonTest.default(...) : requires vector of residuals
bptest:
Error in storage.mode(y) <- "double" :
invalid to change the storage mode of a factor
I imagine I have to restate as an individual probit model for
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