Test Lambda with Beta fixed

Hi dude, I just tested the Lambda level with Beta level fixed. First, I created AR1lambda to test c and d's code. It worked well. Second, I used the same code in the TestData.R. I found out that both c's and d's estimations are always lower than the OLS estimation while sigmalambda2's are higher. c's result is robust under different signal-noise ratio. d's and sigmalambda's estimations improved when signal-noise ratio becomes larger and larger. 

It is worth to notice that the stationary mean is always good no matter what the signal noise ratio is. 
The reason is that both c and d are underestimated. Their effects on the long term stationary mean cancelled because long term mean = c/(1-d).

The stationary variance improved as signal noise ratio increases.  
The reason is that both d and sigmalambda2 improved with better ratio. Long term variance = sigmalambda2/(1-d^2). Therefore the variance improves.

What I have done to code:
1. I fixed a bug that use sigmabeta2 instead of sigmalambda2 when sample d.


My question for you right now is that do we agree that MCMC1 works correctly right now?

Best,
Long