Linear Mixed Models for Chickweight data For a linear mixed model, the model is given as:
$$Y_i = X_i B + Z_i b$$
I know that $B$ denotes the fixed effects estimate and $b$ denotes the random-effects estimates. The $V$ represents the covariance, and the $Z$ is the $n \times q$ design matrix for the random effects relating observations $y$.
I need help in identifying the parameters in this linear mixed model, that is the $b$, $Z$, $B$, and $V$ (variance-covariance) of the model:
model4 <- lmer(weight~Time + Diet + Time*Diet + 
               (1+Time|Chick), 
               data = ChickWeight)
summary(model4)



I need help in identifying the parameters in the linear mixed model. that is the b, Z, B, and V (variance-covariance) of the model?

And from the comments:

For a linear mixed model the model is given as Y_i =X_i*B + Z_i *b. I know that B denotes the fixed effects estimate and b denotes the random-effects estimates. The V represents the covariance. and the Z is the n x q design matrix for the random effects relating observations y. I do not know how to write them out.

You can't write out all of these from just the model formula
As you say above, B is the fixed effects estimates and b is the random effects estimates, both obtained from the fitted model. The values for the matrix V, are also found from the fitted model.
Z is the model matrix for the random effects and this is determined by the data and the study design, not the model formula. If you have fitted the model, then you can extract it with
getME(model4, "Z")

