. Author manuscript; available in PMC: 2022 Jan 1.

Published in final edited form as: Commun Stat Simul Comput. 2018 Feb 28;50(3):881–901. doi: 10.1080/03610918.2019.1571605

Table 1:

Block Co-ordinate Gradient (BCGD) Descent Algorithm

Steps	Algorithm
1.	For j = 1, …,K
	choose ${\hat{β}}_{(j)}^{(0)}$ as initial values.
2.	For the m^th iteration, ${\hat{β}}_{(j)}^{(m + 1)} \leftarrow {\hat{β}}_{l}^{(m)} - γ_{n} \nabla Q_{λ_{n}} ({\hat{β}}_{l}^{(m + 1)})$ with m = 0,1,2,… and γ_n > 0 the step size computed following Armijo rule
3.	For each j, repeat steps 2 until some convergence criterion is met