Maximum likelihood estimation of simple multilevel regression model

I have a two-level regression model:

$$Y_{ij} = \beta_{0j} + \beta_{1j} X_{ij} + \epsilon_{ij},$$ where

$$\beta_{0j} = \gamma_{00} + \gamma_{01} Z_{j} + \mu_{0j},$$ and

$$\beta_{1j} = \gamma_{10} + \gamma_{11} Z_{j} + \mu_{1j}.$$

The question is how can I estimate the parameters via maximum likelihood estimation both Full and restitricted. I need its derivation mathematically if there is any article or book that explain it very clearly.

• 12 symbols appeared in your short writing. But 0 of them has explanation/definition. – user158565 Jul 19 at 1:47