v0.1.4

This version includes:

• Compatibility with the new version 1.4.0 of dbplyr. Documentation also clarifies the possibility of passing dbplyr::simulate_* objects for offline generation of different SQL dialects.

v0.1.3

This version includes:

• Improved tests, including fixes needed after an upgrade to glmnet.

v0.1.2

This version includes:

• Support for the recent refactor of dplyr into dplyr and dbplyr.
• Support for the new Binomial_glm type of object in mboost.

v0.1.1

sqlscore 0.1.1

This version includes:

• Support for cauchit links in glm objects.
• Support for non-Gaussian families in glmboost, specifically: binomial (logit and probit),
  Poisson and gamma.

v0.1.0

The sqlscore package provides utilities for generating sql queries (particularly CREATE TABLE statements) from R model objects. The most important use case is generating SQL to score a GLM or related model represented as an R object, which is particularly when the amount of scoring data is very large.

This version includes:

• Functions to generate CREATE TABLE and SELECT statements from model objects;
• Functions for generating unevaluated R expressions from model objects that correspond to
  • the model's linear predictor
  • the model's final prediction expression (the resposne function of the linear predictor)
• Support for built-in glm and lm objects, as well as
  • bayesglm from package:arm
  • cv.glmnet from package:glmnet
  • glmboost from package:mboost (only Gaussian models)
    Except for glmboost, all link functions that can be represented in SQL are supported for all packages.
• Using a custom link function by name. This is useful if, e.g., your database provides probit or tobit functions.
• Support for various formula features (in particular :, I() and model.matrix-style factor expansion).