## sqlscore 0.1.4
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.

## sqlscore 0.1.3
This version includes:

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

## sqlscore 0.1.2
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.

## 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.

## sqlscore 0.1.0
First release.

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 response 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).
