Changes in Version 0.3-15
o bug fix related to interval estimates in summary()
o improved S3/S4 dispatch for summary.blavaan()
Changes in Version 0.3-14 (and -13)
o fix an error due to bug fix in the Matrix package
Changes in Version 0.3-12 (and -11)
o vector values of wiggle.sd are allowed for different priors on approximate
equality constraints
o logical argument "prisamp" added, for sampling from a model's prior
o for target="stan", lkj prior is used for unrestricted lv correlation matrices
o default priors for conditional approaches (jags and stanclassic) revert to
being placed on precisions (as opposed to sd), for improvement in sampling efficiency
o bug fixes for wiggle argument, stan plot labels,
stanclassic and jags equality constraints, ppmc()
Changes in Version 0.3-10
o save.lvs=TRUE works for missing data under target="stan"
o new arguments "wiggle" and "wiggle.sd" for approximate equality constraints
under target="stan"
o improvements to std.lv=TRUE for target="stan"
o bug fixes for blavCompare() and blavFitIndices()
Changes in Version 0.3-9
o improvements to save.lvs=TRUE for target="stan"
o target="stancond" is added, which is an experimental, noncentered Stan approach.
o bug fixes for prior settings and std.lv in target="stan", and defined parameters.
Changes in Version 0.3-8
o post-estimation, posterior predictive computations have been sped up considerably.
o a number of bug fixes.
Changes in Version 0.3-7
o for target="stan", gamma priors can now be placed on user's choice of
variances, standard deviations, or precisions.
o save.lvs=TRUE now works for target="stan".
o plot() now works uniformly across Stan and JAGS, relying on bayesplot.
o post-MCMC parallelization is now handled via future.apply package
(requires an extra "plan" command from user, but works on windows).
o for target="stan", priors on correlations are now passed through
to Stan (due to previous bug, they were implicitly treated as uniform).
Changes in Version 0.3-6
o bug fix for stan plots, which were silently failing.
Changes in Version 0.3-5
o target="stan" is now the default, using a pre-compiled stan model instead
of "on the fly" code.
o ppmc() function added by Terrence Jorgensen, facilitating posterior
predictive checks.
o default priors are changed from gamma on precisions to gamma on standard
deviations.
o bug fixes: in blavInspect(,"lvmeans") for jags; parameter names in
stan plots.
Changes in Version 0.3-4
o Add function standardizedPosterior() for standardizing posterior draws.
o Rearrange posterior predictive internals.
o Turn off posterior modes for target="jags", due to conflict between current
versions of runjags and modeest.
Changes in Version 0.3-3
o Fix bug in Stan models, where an ov is regressed on an lv (or vice versa) and
std.lv=TRUE.
o Small fixes to blavInspect().
o For convergence="auto", max time was previously 5 min (undocumented).
It is now Inf.
o Axis labels are now more sensible on convergence plots.
o Relative effective sample size now used to compute loo/waic SEs, and SEs
are now returned via fitMeasures().
o Added unit testing via testthat.
o Other bug fixes.
Changes in Version 0.3-2
o Improved handling of Stan models, including missing data, defined variables, 0-variance latents, multi-group.
o Conditional (on latent variables) information criteria available when save.lvs = TRUE.
o Added CITATION to JSS publication and corresponding references updated.
o Experimental function blavFitIndices() added for Bayesian versions of SEM metrics, contributed by Terrence Jorgensen.
o blavaan 'intelligently' chooses target, if either runjags or rstan (but not both) is installed.
o Version dependencies updated, including lavaan and loo.
o Bug fixes from previous version.
Changes in Version 0.3-1
o Stan export/estimation now supported.
o Improved handling of complex models, including growth/change models.
o Logical argument save.lvs added to sample factor scores. Samples/means can be obtained by supplying arguments 'lvs' and 'lvmeans' to blavInspect().
o Bug fixes from previous version.
Changes in Version 0.2-4
o Add 'seed' argument for setting the random seeds in each JAGS chain.
o Bug fixes found in previous version.
Changes in Version 0.2-3
o New function blavCompare() for comparing models via ICs and BFs (code from Mauricio Garnier-Villarreal).
o Defined parameters are now sampled via MCMC, vs estimated via delta method.
o blavInspect() gains 'jagnames' option, showing correspondence between blavaan parameter names and JAGS parameter names.
o Fix bugs in (i) marginal log-lik computation under cp='fa', and (ii) calculated number of parameters under complex equality constraints.
Changes in Version 0.2-2
o Fix bug in 0.2-1 causing model estimation to crash on Windows only.
Changes in Version 0.2-1
o Major update to internals: Model matrices/parameters now correspond to the Lisrel representation used in lavaan.
o General parameter equality constraints using '==' are now available (with one parameter on the lhs).
o New function blavInspect() for extracting various pieces of the MCMC run, including HPDs using an optional 'level' argument.
o JAGS syntax now uses the original observed variable names. It also assigns all prior/constraints to a single parameter vector, then defines model matrices based on this parameter vector.
o A list of user-defined initial values can be supplied via the inits argument.
o Posterior predictive computations are parallelized, if package parallel is installed.
o Improved timings for various parts of the model estimation.
Changes in Version 0.1-4
o New convergence="auto" option to run chains until convergence.
o Bug fixes in model estimation: single-indicator lvs, equality constraints
on exogenous lvs, models with n.chains=1, force runjags parameter summary.
Changes in Version 0.1-3
o Improved support for growth models, including latent variances
fixed to 0.
o Extra monitors supplied via jagextra become defined parameters
in summary().
Changes in Version 0.1-2
o Bayes factors for loadings/regressions now available from
summary() via argument bf=TRUE. These are computed via
the Savage-Dickey density ratio (assuming normal posterior).
o Bug fix in generation of random initial values when some
covariance parameters are fixed to 0 (and we use srs priors).
o Explicit translations from JAGS parameterizations to R
parameterizations. This leads to the availability of
more fitMeasures under a wider variety of priors.
Changes in Version 0.1-1
o Added plot method related to plot.runjags().
o Added argument jagextra for supplying extra code to JAGS.
o Changes to summary():
Improving look and operability with lavaan
Posterior medians/modes now available
o runjags slot in blavaan objects is moved to
@external$runjags.
o fitMeasures() now includes BIC and loglik (at posterior means).
o do.fit=FALSE now works, returns only JAGS syntax.
o Random initial values less likely to fail.
o Bug fixes related to equality constraints on mv variances +
std.lv=T vs TRUE.