I asked a question earlier on here.
Essentially, I am trying to evaluate a warning system that consists of a light bulb (of a specific color) being switched on, to indicate a predicted warning threat level. Srikant came up with a simple solution which involved calculating the posterior probabilities of the warning system, using bayes theorem.
I am now contemplating implementing this in R. However, I am not quite sure how to proceed, since I am an R newbie.
The data looks like this:
warning light, event level occured? red, yes none, yes green, no etc ...
I would like to write a simple R script that will help me to calculate:
a). the posterior probablity of an event occuring, for a given state of the light bulb b). a C.I to attach to the posterior probability obtained in (a) above
Since I am new to R, I would be grateful for the steps (and commands) required to do the above. My data will be in a simple csv file in the format described, so I can simply scan() it into R. How to proceed from there, is what I need help with..