Parameter Estimation 。General setting: -Given a(hypothesized probabilistic)model that governs the random experiment -The model gives a probability of any data p(D) that depends on the parameter 0 -Now,given actual sample data X={x1,..,xn},what can we say about the value of 0? Intuitively,take your best guess of 0--"best" means“best explaining/fitting the data” Generally an optimization problem CCF-ADL at Zhengzhou University, 11 June25-27,2010 CCF-ADL at Zhengzhou University, June 25-27, 2010 11 Parameter Estimation • General setting: – Given a (hypothesized & probabilistic) model that governs the random experiment – The model gives a probability of any data p(D|) that depends on the parameter  – Now, given actual sample data X={x1 ,…,xn }, what can we say about the value of ? • Intuitively, take your best guess of  -- “best” means “best explaining/fitting the data” • Generally an optimization problem