grad_gmic: Gradient Function for gMIC
In liqun730/gMIC: Group Sparsity via Approximated Information Criteria

Gradient Function for gMIC

1	grad_gmic(X, y, a, lambda, gamma, group, family)

`X`	The design matrix.
`y`	The response vector
`a`	The approximation parameter for gMIC.
`lambda`	The gMIC penalization parameter.
`gamma`	The optimization parameter.
`group`	The group structure of the model. For example, assume that X has 4 columns and group=c(1,1,2,2). It means the first 2 features form a group of variables and the last 2 features form another group of variables.
`family`	The type of glm model, should be one of "gaussian", "binomial" or "poisson".