BAS 1.4.7 October 22, 2017

Updates

BAS 1.4.6 May 24, 2017

Updates

Bugs

BAS 1.4.5 March 28, 2017

Bugs

BAS 1.4.4 March 14, 2017

Updates

Bugs

BAS 1.4.3 February 18, 2017

Updates

Bug fixes

BAS 1.4.2 October 12, 2016

Updates

Bug Fixes

BAS 1.4.1 September 17, 2016

Bug Fixes

Features

BAS 1.4.0 August 25, 2016

New features

BAS 1.3.0 July 15, 2016

New Features

A vignette has been added at long last! This illustrates several of the new features in BAS such as

Deprication

BAS 1.2.2 June 29, 2016

New Features

Minor Changes

BAS 1.2.1 April 16, 2016

BAS 1.2.0 April 11, 2016

BAS 1.1.0 March 31, 2016

New Features

Minor Changes

BAS 1.09

- added weights for linear models
- switched LINPACK calls in bayesreg to LAPACK finally should be
faster
- fixed bug in intercept calculation for glms
- fixed inclusion probabilities to be a vector in the global EB
methods for linear models

BAS 1.08

- added intrinsic prior for GLMs
- fixed problems for linear models for p > n and R2 not correct

BAS 1.07

- added phi1 function from Gordy (1998)  confluent hypergeometric
function of two variables  also known as one of the Horn
hypergeometric functions or Humbert's phi1
- added Jeffrey's prior on g
- added the general tCCH prior and special cases of the hyper-g/n.
- TODO check shrinkage functions for all    

BAS 1.06

- new improved Laplace approximation for hypergeometric1F1
- added class basglm for predict
- predict function now handles glm output
- added dataframe option for newdata in predict.bas and predict.basglm
- renamed coefficients in output to be 'mle' in bas.lm to be consistent across
lm and glm versions so that predict methods can handle both
cases.  (This may lead to errors in other external code that
expects object$ols or object$coefficients)
- fixed bug with initprobs that did not include an intercept for bas.lm

BAS 1.05

- added thinning option for MCMC method for bas.lm
- returned posterior expected shrinkage for bas.glm
- added option for initprobs = "marg-eplogp" for using marginal
SLR models to create starting probabilities or order variables
especially for p > n case
- added standalone function for hypergeometric1F1 using Cephes
library and a Laplace aproximation
-Added class "BAS" so that predict and fitted functions (S3
methods) are not masked by functions in the BVS package: to do
modify the rest of the S3 methods.

BAS 1.04

- added bas.glm for model averaging/section using mixture of g-priors for
GLMs.  Currently limited to Logistic Regression
- added Poisson family for glm.fit

BAS 1.0

- cleaned up  MCMC method code

BAS 0.93

- removed internal print statements in bayesglm.c
- Bug fixes in AMCMC algorithm

BAS 0.92

- fixed glm-fit.R  so that hyperparameter for BIC is numeric

BAS 0.91

- added new AMCMC algorithm

BAS 0.91

- bug fix in bayes.glm

BAS 0.90

- added C routines for fitting glms

BAS 0.85

- fixed problem with duplicate models if n.models was > 2^(p-1) by

restricting n.models

- save original X as part of object so that fitted.bma gives the

correct fitted values (broken in version 0.80)

BAS 0.80

- Added `hypergeometric2F1` function that is callable by R
- centered X's in bas.lm so that the intercept has the correct

shrinkage - changed predict.bma to center newdata using the mean(X) - Added new Adaptive MCMC option (method = “AMCMC”) (this is not stable at this point)

BAS 0.7

-Allowed pruning of model tree to eliminate rejected models

BAS 0.6

- Added MCMC option to create starting values for BAS (`method = "MCMC+BAS"`)

BAS 0.5

-Cleaned up all .Call routines so that all objects are duplicated or

allocated within code

BAS 0.45

- fixed ch2inv that prevented building on Windows in bayes glm_fit

BAS 0.4

- fixed fortran calls to use F77_NAME macro 
- changed  allocation of objects for .Call to prevent some objects from being overwritten.  

BAS 0.3

- fixed EB.global function to include prior probabilities on models
- fixed update function 

BAS 0.2

- fixed predict.bma to allow newdata to be a matrix or vector with the

column of ones for the intercept optionally included. - fixed help file for predict - added modelprior argument to bas.lm so that users may now use the beta-binomial prior distribution on model size in addition to the default uniform distribution - added functions uniform(), beta-binomial() and Bernoulli() to create model prior objects - added a vector of user specified initial probabilities as an option for argument initprobs in bas.lm and removed the separate argument user.prob