Algorithm 1.

BCD Algorithm for solving the optimization in (26) in the M-step of the proposed EM framework

Input: ${\mathit{S}}_{\mathrm{i}}$ for each subject, $i=1,\dots ,N$; ${ }^{\left(t\right)}\mathbf{\Theta }$ from the $t$-th EM iteration; $\mathit{C}$ and $\mathbf{Z}$; tuning parameters $\mathrm{\lambda }$, $\mu$, $h$; stopping criterion, ${\mathrm{ϵ}}_{BCD}.$
Output: updated ${ }^{\left(t+1\right)}\mathbf{\Theta }$.
1.	Initialize: ${\mathbf{\Theta }}^0\leftarrow { }^{\left(t\right)}\mathbf{\Theta };k\leftarrow 0\mathrm{ };$
2.	Compute $\mathbf{H}=\mathbf{H}\left({ }^{\left(t\right)}\mathbf{\Theta }\right)$ using Equation (19);
3.	Repeat
4.	Let ${\mathbf{\Theta }}^{k+1}={\mathbf{\Theta }}^k$;
5.	for $j=1$ to $p$ do
6.	Partition ${\mathbf{\Theta }}^{k+1}$, $\mathbf{H}$, $\mathit{C}$ and $\mathbf{Z}$ for $j$-th column/row according to according to (27) - (28), respectively;
7.	Solve the optimization in (29) to get $\alpha$ and ${\mathbf{\Theta }}_j$;
8.	Compute ${\mathrm{\theta }}_{jj}^{k+1}$ using (33) and ${\mathbf{\Theta }}_j^{k+1}={\mathbf{\Theta }}_j$;
9.	Update the $j$-th column/row of ${\mathbf{\Theta }}^{k+1}$ by ${\mathbf{\Theta }}_j^{k+1}\mathrm{ }$ and ${\mathrm{\theta }}_{jj}^{k+1}$;
10.	End for
11.	$k\leftarrow k+1$;
12.	until $\left|\left|{\mathbf{\Theta }}^{k+1}-{\mathbf{\Theta }}^k\right|\right|\le {\mathrm{ϵ}}_{BCD}\mathrm{ }$
13.	${ }^{\left(t+1\right)}\mathbf{\Theta }\leftarrow {\mathbf{\Theta }}^{k+1}$.