LoglikPenGLM: Compute the penalized log likelihood for GLM with MIC penalty...
In liqun730/gMIC: Group Sparsity via Approximated Information Criteria

Compute the penalized log likelihood for GLM with MIC penalty via R function glm

1 2	LoglikPenGLM(gamma, group, X, y, lambda, a, family = gaussian(link = "identity"))

`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.
`X`	An n by p design matrix.
`y`	The n by 1 response vector
`lambda`	The penalty parameter euqals either 2 in AIC or ln(n) in BIC (by default). It can be specified as any value of the user's own choice.
`a`	The scale parameter in the hyperbolic tangent function of the MIC penalty. By default, a = 50.
`family`	a description of the error distribution and link function to be used in the model. It needs to be the result of a call to a family function since `glm.fit` is used here. In other words, it can NOT be specified as a character string naming a family function nor a family function. See `glm` and `family` for details of family functions.
`beta`	A p-dimensional vector containing the regression ceofficients.