Version 0.7.2
------------------------------

MINOR CHANGES

  - Updated examples for ggs_pairs() to work with newer version of GGally.

  - GGally is imported instead of depends.

  - Specify a certain version of tidyr (0.3.1 needed)

  - Add a check that "Parameter" is a factor, which is not granted with the
  development version of tidyr as of 04/01/2016.


Version 0.7.2
------------------------------

MINOR CHANGES

  - Solve revdep issue with tidyr-0.3 due to unqualified imports of "%>%, and
  use explicit calls to dplyr and tidyr in all functions taken from those packages.

  - Improve citation.

  - Improve the text of the package description.

  - Add BugReports fields and include another URL.


Version 0.7.1
------------------------------

MINOR CHANGES
  
  - Minor changes to pass CRAN checks.


Version 0.7
------------------------------

MAJOR CHANGES

  - Added new function ggs_pairs() (thanks to Max Joseph) that produces
  scatterplot matrices of parameters, helping with posterior correlation.
  Library GGally is now a dependency.

  - ggs() is now able to process warmup (burnin) samples from stan, and so the
  argument "inc_warmup" now does something useful.


MINOR CHANGES

  - ci() does not allow lists of data frames, so change it accordingly in the
  help file (thanks to Alex Zvoleff).

  - Solve minor issues with par_labels.

  - Solve minor issue with ggs_crosscorrelation not showing correctly par_labels
  (thanks to Juste).

  - Add a small example to the documentation about the use of the family
  argument in ggs().

  - Better specify the origin of dplyr::* functions, to avoid collisions with
  other packages.


Version 0.6
------------------------------

MAJOR CHANGES

- Include data and samples from models in order to facilitate examples

  linear: MCMC output from a linear regression model with dummy data.

  logit: MCMC output from a logit regression model with dummy data.

  radon: MCMC output and other description variables for a hierarchical /
  multilevel model based on radon example at Gelman & Hill.

- Major revision of the code moving plyr to dplyr and reshape2 to tidyr

  The main object from ggs() is no more a data frame, but a tbl_df.

  Deleted the possibility of parallelization. It is not (yet) implemented in
  dplyr, but in any case, dplyr is clearly faster than plyr.

- New function ci() that calculates credible intervals for a ggs() object.

- When using par_labels, not only the columns "Parameter" and "Label" are
  considered, but also the resulting ggs() object contains other columns present
  in par_labels and the old Parameter name. This allows mainly ggs_caterpillar()
  (but also other functions) to use facets or colors, fills, etc.

- New argument "simplify" in ggs_traceplot() or "simplify_traceplot" in ggmcmc()
  that allows to keep only a percentage of random chains, so that the size of the
  plot (and the time taken) is reduced considerably. But use it with care, because
  then the chain is no more complete.

- Homogenize function names, using underscores "_" everywhere, instead of dots
  ".", in calc_bin(), gl_unq() and roc_calc().



MINOR CHANGES

- When selecting a family of parameters, maintain parameter ordering for
  multipage outputs.

- par_labels had a bug that produced wrong reordering of labels, and levels of
parameters were incorrectly sorted. Although it is a minor change, the mistake
was severe.

- Labels in x-axis in crosscorrelation matrix are better aligned and more
  legible.

- Solve scaling issues in Rhat. Introduce a meaningful default.

- Better examples for ggs_separation() and ggs_rocplot().

- Documentation improved for internal functions.


Version 0.5.1
------------------------------

MINOR CHANGES

- When the chain is stucked in the same value, the computation of the ar() for
  the spectral density needed by ggs_geweke() failed. It has been solved

- When the range of a parameter is huge the calculation of the bins is
  approximate, and gave different number of bins. Now ggs_histogram takes care of
  different number of bins by each variable due to rounding.


Version 0.5
------------------------------

MAJOR CHANGES

- ggmcmc() now allows the argument "plot" to 

- ggs_Rhat() now has scaling between 1 and 1.5 by default, so that perspective
  on real convergence is present. 

- ggs_geweke() includes anargument shadow_limit to highlight the -2+2 range

- rugs in ggs_density() and ggs_compare_partial() are FALSE by default: rug it
  is only a visual improvement that really does not add too much information to
  the plot, but it takes a lot of resources.


MINOR CHANGES

- Old arguments "param.page" from ggmcmc() and "fully.bayesian" from
  ggs_rocplot() now use underscore to be systematic with the rest of the package.

- Change default label for ggs_histogram().

- Rhat label now has a real hat.


Version 0.4.2
------------------------------

MINOR CHANGES

- Bug in ggmcmc() related to ggs_histogram() and the division in pages relying
  on nParameters.


Version 0.4.1
------------------------------

MINOR CHANGES

- Bug in export on ggs_rocplot.

- Stan samples are imported without relying on coda.


Version 0.4
------------------------------

MAJOR CHANGES

- Add the possibility to use different parameter names than the default ones
  provided by the MCMC software, using the argument "par_labels" in ggs().

- Move from reshape() to reshape2().

- geom_histogram() allows to specify a desired number of bins.

- ROC plot (ggs_rocplot()) with code originally from Zachary M. Jones.

- Separation plot (ggs_separation()) with code originally from Zachary M. Jones.

- New plots ggs_ppmean() and ggs_ppsd() for posterior predictive checks.

- Make parallel=FALSE the default in ggs().

- Consistency in names of the arguments achieved by moving all "." into "_".

MINOR CHANGES

- rstan is no more a suggested package, because it is not in CRAN, and it is
  not expected to be there in the near future.

- Fix bugs in ggs_crosscorrelation when the number of parameters was 1 or 2.

- In ggmcmc, do not plot Potential Scale Reduction Factor when there is a
  single chain.

- Allow NULL as filename for the pdf file in ggmcmc.

- argument "labels" in ggs_caterpillar() is renamed to "model_labols" avoid
  confusion with the parameter names

- Adjust the defaults for the caterpillar plots, to remark the thick and thin
  segments


Version 0.3
------------------------------

MAJOR CHANGES

- ggs() can import MCMCpack objects, stanfit objects and csv files from Stan
  running from the command line, in addition to the previous import of samples
  from mcmc.list() objects (from the coda package).

- New functions ggs_Rhat() and ggs_geweke() that show graphically the results
  of the Rhat (potential scale reduction factor, by Gelman & Rubin), and the
  Geweke diagnostic (z-score).

- ggs_caterpillar is able to plot against a continuous variable due to the
  addition of the 'X' argument

- ggs_caterpillar() has the ability to plot two models, so that model
  comparison is easier. Thanks to Zachary M. Jones.

- New parameter "family" that allows to select only certain parameters from
  the ggs object based on a regular expression (i.e., select all "beta"
  parameters, or all "theta", ones, or "alpha\\[1,.\\]", etc...)

MINOR CHANGES

- Traceplot now shows by default the burnin period and takes care of the
  thinning, used by ggs_traceplot() and ggs_running().

- New argument to have absolute colour scale in crosscorrelations.

- ggs_caterpillar() is horizontal by default.

- Documentation has been improved.


Version 0.2
------------------------------

MINOR CHANGES

- opts() is replaced by theme() as it is deprecated in ggplot-0.9.2.

- theme_text() is replaced by element_text() as it is deprecated in
  ggplot-0.9.2.

- opts(title="") is replaced by labs(title="") as it is deprecated in
  ggplot-0.9.2.


Version 0.1
------------------------------

Initial version
