Holistic Generalized Linear Models
Obtain all Active Coefficients
Aggregate Binomial Data
Convert to OP
Extract Model Coefficients
Construct Covariance matrix
Group Equal Constraint
In-Out Constraint
Group Sparsity Constraint
Fitting Holistic Generalized Linear Models
Fitting Holistic Generalized Linear Models
Create a HGLM Model
Generic Functions for hglmc Objects
Holistic Generalized Linear Models Package
Include Constraint
Constraint on the Number of Covariates
Linear Constraint
Lower Bound
Pairwise Sign Coherence
Predict Method for HGLM Fits
Objects exported from other packages
Random HGLM Data
Constraint on the Pairwise Correlation of Covariates
Scale Linear Constraint Matrix
Sign Coherence Constraint
Extract Solution
Update the Model Object
Upper Bound
Holistic generalized linear models (HGLMs) extend generalized linear models (GLMs) by enabling the possibility to add further constraints to the model. The 'holiglm' package simplifies estimating HGLMs using convex optimization. Additional information about the package can be found in the reference manual, the 'README' and the accompanying paper <doi:10.18637/jss.v108.i07>.