In fact I am reading a paper about Microsoft's Adpredictor model. And here is a web article about the model's derivative process.
In the Step 7 of the web article, the author says that :
p(t) = N(t; μ, σ2)δ(y = sign(t)) and when y = 1, p(t) = N(t; μ, σ2)δ(t > 0) and then t has a truncated...
I have a Gaussian distribution about t, say, N(t; μ, σ), and a a Dirac Delta Function δ(t).
Then how can I compute: N(t; μ, σ) * δ(t > 0)
Any clues? Or recommender some materials for me to read?
Thanks!