BAS Version 1.5.2

BAS 1.5.2

Features

• Included an option pivot=TRUE in bas.lm to fit the models using a pivoted Cholesky decomposition to allow models that are rank-deficient. Enhancment #24 and Bug #21. Currently coefficients that are not-estimable are set to zero so that predict and other methods will work as before. With more testing and timing this may become the default; otherwise the default method without pivoting issues a warning if log marginals are NA. The vector rank is added to the output (see documenation for bas.lm) and the degrees of freedom methods that assume a uniform prior for obtaining estimates (AIC and BIC) are adjusted to use rank rather than size.

• Added option force.heredity=TRUEto force lower order terms to be included if higher order terms are present (hierarchical constraint) for method='MCMC' and method='BAS' with bas.lm and bas.glm. Updated Vignette to illustrate. enhancement #19. Checks to see if parents are included using include.always pass issue #26.

• Added option drop.always.included to image.bas so that variables that are always included may be excluded from the image. By default all are shown enhancement #23

• Added option drop.always.included and subset to plot.bas so that variables that are always included may be excluded from the plot showing the marginal posterior inclusion probabilities (which=4). By default all are shown enhancement #23

• update fitted.bas to use predict so that code covers both GLM and LM cases with type='link' or type='response'

• Updates to package for certification

• Added Code Coverage support and more extensive tests using test_that.

Bugs

• fixed issue #36 Errors in prior = "ZS-null" when R2 is not finite or out of range due to model being not full rank. Change in gexpectations function in file bayesreg.c

• fixed issue #35 for method="MCMC+BAS" in bas.glm in glm_mcmcbas.c when no values are provided for MCMC.iterations or n.models and defaults are used. Added unit test in test-bas-glm.R

• fixed issue #34 for bas.glm where variables in include.always had marginal inclusion probabilities that were incorrect. Added unit test in test-bas-glm.R

• fixed issue #33 for Jeffreys prior where marginal inclusion probabilities were not renomalized after dropping intercept model

• fixed issue #32
  to allow vectorization for phi1 function in R/cch.R
  and added unit test to "tests/testthat/test-special-functions.R"

• fixed issue #31 to coerce g to be a REAL for g.prior prior and IC.prior in bas.glm; added unit-test "tests/testthat/test-bas-glm.R"

• fixed issue #30 added n as hyperparameter if NULL and coerced to be a REAL for intrinsic prior in bas.glm; added unit-test

• fixed issue #29 added n as hyperparameter if NULL and coerced to be a REAL for beta.prime prior in bas.glm; added unit-test

• fixed issue #28 fixed length of MCMC estimates of marginal inclusion probabilities; added unit-test

• fixed issue #27 where expected shrinkage with the JZS prior was greater than 1. Added unit test.

• fixed output include.always to include the intercept issue #26 always so that drop.always.included = TRUE drops the intercept and any other variables that are forced in. include.always and force.heredity=TRUE can now be used together with method="BAS".

• added warning if marginal likelihoods/posterior probabilities are NA with default model fitting method with suggestion that models be rerun with pivot = TRUE. This uses a modified Cholesky decomposition with pivoting so that if the model is rank deficient or nearly singular the dimensionality is reduced. Bug #21.

• corrected count for first model with method='MCMC' which lead to potential model with 0 probabiliy and errors in image.

• coerced predicted values to be a vector under BMA (was a matrix)

• fixed size with using method=deterministic in bas.glm (was not updated)

• fixed problem in confint with horizontal=TRUE when intervals are point mass at zero.

Other

• suppress warning when sampling probabilities are 1 or 0 and the number of models is decremented
  Issue #25

• changed force.heredity.bas to renormalize the prior probabilities rather than to use a new prior probability based on heredity constraints. For future, add new priors for models based on heredity. See comment on issue #26.

• Changed License to GPL 3.0

BAS 1.5.1

BAS 1.5.1 June 6, 2018

Features

• added S3 method variable.names to extract variable names in the highest probability model, median probability
  model, and best probability model for objects created by predict.

Bugs

• Fixed incorrect documentation in predict.basglm which had that type = "link" was the default for prediction issue #18

BAS 1.5.0

BAS 1.5.0 May 4, 2018

Features

• add na.action for handling NA's for predict methods; GitHub issue #10

• added include.always as new argument to bas.lm. This allows a formula to specify which terms should always be included in all models. By default the intercept is always included.

• added a section to the vignetted to illustrate weighted regression and the force.heredity.bas function to group levels of a factor so that they enter or leave the model together.

Bugs Fixes

• fixed problem if there is only one model for image function;
  GitHub issue #11

• fixed error in bas.lm with non-equal weights where R2 was incorrect. GitHub issue #17

Deprecated

• deprecate the predict argument in predict.bas, predict.basglm and internal functions as it is not utilized

BAS Version 1.4.9

Version of BAS to accompany final version of the paper "Mixtures of g-priors in Generalized Linear Models" to appear in the Journal of the American Statistical Association.

BAS Version 1.4.2

Version of BAS to accompany latest version of the paper "Mixtures of g-priors in Generalized Linear Models"

BAS Version 1.4.1

Bug Fixes

• the modification in 1.4.0 to automatically handle NA's led to
  errors if the response was transformed as part of the forumula;
  this is fixed in this release

New Features

• added subset argument to bas.lm and bas.glm so that arguments match standard lm and glm in R

Added DOI from Zenodo

BAS version 1.4.0

New features

• added na.action for bas.lm and bas.glm to omit missing data.
• new function to plot credible intervals created by confint.pred.bas or confint.coef.bas. See the help files for an example or the vignette.
• added se.fit option in predict.basglm.
• Added testBF as a betaprior option for bas.glm to implement Bayes Fatcors based on the likelihood ratio statistic's distribution for GLMs.

v1.3.1

The latest release adds the following new features:

• added na.action for bas.glm to handlemissing data.
• new function to plot credible intervals created by confint.pred.bas or confint.coef.bas. See the help files for an example or the vignette.
• added se.fit option in predict.basglm.
• Added testBF as a betaprior option for bas.glm to implement Bayes Factors based on the likelihood ratio statistic's distribution for GLMs.

BAS version 1.3.0 Coursera Release

Release of BAS package version 1.3.0 for Launch of Coursera course on Bayesian Statistics