I am reading: Maximum likelihood estimation of mean reverting processes Jose Carlos Garca Franco,
My questions is simply: I have a Ornstein-Uhlenbeck SDE, which I find the mean and variance of:
Now given a conditional normal pdf I can plug in expected value and variance and get:
Now what I don't get is what has been done to get ($t_i$ - $t_i$$-$$_1$)
and what does it mean, if $f_1$$_0$ has x at time $t_i$ = $t_1$$_0$ and in for example in the part $e$^2n($t_1$$_0$-$t_9$), what would this imply.
It would help me a lot if someone could help me understand what this mean, and if there is anything I could do to improve the question please give me some feedback. I really want to understand this so any help will be much appreciated.