# glmbayes 0.9.3

* Version bump in response to CRAN resubmission feedback.

# glmbayes 0.9.2

* Version bump in preparation for resubmission incorporating CRAN review feedback.

# glmbayes 0.9.1

* Wrapped OpenCL-dependent examples in `\donttest{}` for CRAN compliance.
* Reduced iteration counts in rlmb Gibbs sampler example to stay within
  CRAN example time limits on slower check machines.

# glmbayes 0.9.1

First CRAN submission. This release is a stable pre-release with a
near-complete feature set relative to earlier development builds.

## Highlights

### Bayesian Generalized Linear (glmb) and Linear (lmb) modeling functions:

  `glmb()` is a Bayesian analog for the classical `glm()` function while
  `lmb()` covers Gaussian models. Calls largely mirror those for the 
  classical functions but leverage pfamilies for prior specifications.
  Method functions largely mirror those for the classical functions. 
  Samples generated by the functions are largely iid samples 
  (no MCMC convergence dignostics are needed).

### Implemented Likelihood families/ link functions:
   
  Most of the families implemented in the `glm()` function are also implemented 
  in the `glmb()` function (the `lmb()` function covers only gaussian() families). 
  Link functions that lead to log-concave likelihood functions are generally 
  implemented.  Specifically, we have the following:
  
  **Supported likelihoods:** gaussian (identity), Poisson / quasi-Poisson
  (log), binomial / quasi-binomial (logit, probit, cloglog), Gamma (log).

### Prior Family functions:

 `pfamily` constructors are used to specify priors and play the same
  kind of role for the prior specifications as `family` constructors 
  and `link` functions play for the likelihoods. Specifically, we
  have the following:

  **Supported Priors:** Normal (all families/links), Normal–Gamma and 
  independent Normal–Gamma (gaussian families), and Gamma-on-precision 
  (gaussian and Gamma families).
  
### Prior_Setup function:
 
  The package comes with a convenient `Prior_Setup()` function that provides 
  default prior input parameters for each of the implemented models. Basic calls
  (without tailoring) mirror traditional calls to the `glmb()` and `lmb()`
  functions respectively and only require the user to provide the model formula
  and (if not the gaussian family) the family/link function. 
  
  The function can also be used to easily adjust prior specifications 
  (see documentation for details).
  
### Extensive Method functions:
  
  The package comes with extensive method functions that mirror those 
  for the classical functions.  These include dedicated `print()`,
  `summary()`, `predict()` and `simulate()` functions.

### Lower Level Modeling functions:

  The package comes with lower level modeling/simulation functions
  that advanced users can use to implement block Gibbs samplers. These
  generally come with less overhead than the `glmb()` and `lmb()` functions 
  and are called internally by the the higher level modeling functions.

### RcppParallel and OpenCL GPU Acceleration Implementations
  
  Some of the simulation functions comes with use_parallel and use_opencl options
  that speed up simulation for higher dimensional models.
  
### Extensive help files, vignettes, examples and demos

  The package also comes with extensive help files for the varios functions 
  that are complemented with a rich set of vignettes. A large number of 
  examples and demos are also availabel (see the READM.md file for a sample).

---

## Earlier development history (0.1.x series)

The notes below summarize major work during the initial development series
before the 0.9.0 pre-release.

### OpenCL and GPU acceleration

- Completed the OpenCL-based grid construction framework for large models.
- Added GPU-aware envelope sizing and improved OpenCL failure handling.
- Introduced diagnostic utilities to assess OpenCL availability and
  performance.
- Improved configure scripts to detect OpenCL and provide informative
  messages.
- Expanded OpenCL documentation and added a dedicated vignette chapter.

### Parallel CPU sampling (RcppParallel)

- Enabled parallel envelope construction and parallel iid sampling.
- Added pilot functions for large-dimension grid estimation.
- Implemented thread-safe parallel sampling for independent normal-gamma
  models.

### Core statistical improvements

- Migrated to an improved independent normal-gamma simulation algorithm.
- Added theoretical derivations for independent normal-gamma regression.
- Improved UB2 and RSS minimization routines, including scaling corrections.
- Enhanced `Prior_Setup()` to support family-specific prior construction.
- Added dedicated envelope evaluation and sizing functions.

### Package infrastructure

- Significant cleanup to remove NOTES and improve CRAN readiness.
- Improved configure and Makevars files for portability.
- Added testthat tests, including OpenCL-specific tests.
- Consolidated envelope-building functions into a cleaner structure.

### Documentation

- Major updates to README and package-level documentation.
- Added multiple new vignettes and expanded existing ones.
- Improved examples for `lmb()`, `rlmb()`, and OpenCL models.

### Bug fixes (0.1.x era)

- Corrected scaling in UB2 minimization.
- Improved error handling for missing OpenCL functionality.
- Fixed various small issues uncovered during parallelization work.
