[R-sig-ME] glmmTMB's variance-covariance matrix is of the vector of observed intercept per subject minus the quantity of the fixed intercept plus the random-intercept term?

[Sun, John]

Dear All,

I am writing to ask which random-vector glmmTMB estimates the variance-covariance matrix. Is the random-vector that glmmTMB the G-matrix Charles Roy Henderson describes in https://en.wikipedia.org/wiki/Mixed_model?

Suppose we have a model with random-intercepts and fixed-effects. Is the random-vector that glmmTMB estimates the variance-covariance of equal to the actual random-intercept of the individual minus the quantity of the random-effect plus the fixed-intercept effect?

The random-intercept for some individual equals the intercept's random-effect plus the fixed-effect of the intercept plus some random-error scalar drawn from a normal distribution. 
I refer to the equation in the second level of the two-level model. 

The level one equation equals alpha_i+beta*Xij + epsilon_i. 
The level two: alpha_i=delta+gamma_i + h_i.

"I" is subject, j is timepoint. Delta is fixed-intercept term, gamma_i is individual's deviation from the fixed-intercept. h_i is some deviation of the individual from the fixed-effect drawn from some normal distribution. 

Best regards,
John