Accurate Generalized Linear Model
Class for results of aglm() and cv.aglm()
S4 class for input
aglm: Accurate Generalized Linear Model
Fit an AGLM model with no cross-validation
Get coefficients
Create bins (equal frequency binning)
Create bins (equal width binning)
Fit an AGLM model with cross-validation for
Class for results of cva.aglm()
Fit an AGLM model with cross-validation for both and $\lambda...
Get deviance
Binning the data to given bins.
Create L-variable matrix for one variable
Create a O-dummy matrix for one variable
Create a U-dummy matrix for one variable
Plot contribution of each variable and residuals
Make predictions for new data
Display textual information of the model
Get residuals of various types
Provides functions to fit Accurate Generalized Linear Model (AGLM) models, visualize them, and predict for new data. AGLM is defined as a regularized GLM which applies a sort of feature transformations using a discretization of numerical features and specific coding methodologies of dummy variables. For more information on AGLM, see Suguru Fujita, Toyoto Tanaka, Kenji Kondo and Hirokazu Iwasawa (2020) <https://www.institutdesactuaires.com/global/gene/link.php?doc_id=16273&fg=1>.