1. Statistics
2. Correlation and Regression Analysis
3. Linear Regression
4. Ordinary Least Squares
5. 518518

This content was COPIED from BrainMass.com - View the original, and get the already-completed solution here!

Let {x_n} be an observed random process which is generated by the following nonlinear recursion

x_n = (theta_1)(x_n-1) + (theta_2g)(x_n-2, x_n-3) + w_n

where {w_n} is an i.i.d. zero-mean sequence and g(.,.) is a known deterministic function. We are interested in estimating the two parameters theta_1, theta_2. (a) Propose a fixed sample size and an adaptive estimator for the parameter vector [theta_1, theta_2] that does not require knowledge of the statistics of {w_n}. (b) Analyze the convergence properties of your adaptive estimator.