Variance component estimation

In the previous analysis, I used 50,000 iterations to compute variance components and heritability. However, to have a firm conclusion, I rerun with 250,000 iterations. Thus there are two sets of variance components and heritability estimates one for each iteration value.

Heritability

In general the estimate of heritability is lower when using 250,000 iteration. The difference is larger for wt_2top (0.358 vs 0.403). The difference (using iteration 250,000 vs 50,000) decreases as age of the Scaled weight increases, for example at year 2 heritability for scaled live body weight wt_2sw (0.568 vs 0.592) and at year 5: heritabilitty for scaled live body weight swt_5sw (0.634 vs 0.636).

Additive genetic and residual variance-covariance components

The only significant difference I observe in the variance covariance part is for wt_2top. The Genetic variance was 445 using 250,000 iteration and 506 using 50,000 iteration, however the residual variance showed reverse trend that is using 250,000 iterations 799 and using 50000 iteration 751. All in all at younger age ( year2 ), the estimate of the genetic and non-genetic parameter differ a bit but at older ago I got similar result regardless of the iteration. I will plot MMC sample distribution and we can decide to write the paper using 250,000 iterations or 50,000 iteration or may be to analyse as a bivariate model ( n(n-2)/2 analysis combination) if the MCMC sample distribution does not converge.