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
2.1 1、Statistical or random experiment 2、Sample space or population Sample point, event 2.2 Stochastic or random variable (r. v.) 2.3 Probability 2.4 R.V. and probability density function
General linear models Suppose that we have a model: 1 It is inherently linear for the parameters if it can be transformed into Examples: 1. Exponential model: Y