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.
