Chapter 12 Time Series Analysis 12.1 Stochastic processes A stochastic process is a family of random variables {Xt,t ET}. Example{St,t 0, 1,2,...} where St i=o X; and iid(0,2). St has a different distribution at each point t
Chapter 4 Finite-Sample properties of the LSE Finnite-sample the n is assumed to be fixed normal dist n assumed Large-sample theory n is sent to oo, general distn assumed
Expectations and Conditional Expectations Definition 1 Discrete Random Variable random wariable is discrete f the set of outcomes is either finite in number or countably
LAW OF ITERATED EXPECTATIONS Law of Iterated Expectations Theorem 1 Law of iterated expectation.s The notation Er[ indicates the expectation over the value of a Example