(This article was first published on

**Statistical Modeling, Causal Inference, and Social Science » R**, and kindly contributed to R-bloggers)The Stan Development Team is happy to announce that Stan 1.3.0 and RStan 1.3.0 are available for download. Follow the links on:

- Stan home page: http://mc-stan.org/

Please let us know if you have problems updating.

Here’s the full set of release notes.

v1.3.0 (12 April 2013) ====================================================================== Enhancements ---------------------------------- Modeling Language * forward sampling (random draws from distributions) in generated quantities * better error messages in parser * new distributions: + exp_mod_normal + gumbel + skew_normal * new special functions: + owenst * new broadcast (repetition) functions for vectors, arrays, matrices + rep_arrray + rep_matrix + rep_row_vector + rep_vector Command-Line * added option to display autocorrelations in the command-line program to print output * changed default point estimation routine from the command line to use Nesterov's accelerated gradient method, added option for point estimation with Newton's method RStan * added method as.mcmc.list() * compatibility with R 3.0.0 C++/Internal * refactored math/agrad libs in C++ to separate files/includes, remove redundant code, more unit tests for existing code * added chainable_alloc class for caching solver results * generalized VectorView with seq_view * templated out generated code for efficient double-only operation on model log probs w/o gradients Doc * additions to user's guide w. sample models + stochastic volatility example with source, optimized source, simulation + time series, moving average, standardization for linear regression, hidden Markov models, with examples * manual's index is now hyperlinked * added additional acknowledgements to manual * added full description of differences between sampling statement and lp__ * fixed general normal mixture model example Testing * split unit tests from distribution tests Bug Fixes ---------------------------------- * fixed derivative in multi_normal_prec distribution function * double-based log_prob functions return the same value as var-based log_prob_grad functions * calls to lgamma are now using boost's lgamma function * patched transform to work with Eigen 3.2 beta * all probability distribution functions and cumulative distribution functions behave properly with 0 length vector arguments * fixed error in definition of hypergeometric pmf * fixed arguments to nesterov optimization ctor in command * fixed issue with initialization matrices being read improperly * Use fabs() instead of abs() in unit_vector_constrain. * typos in the manual * rstan: + fixed crash in R when index is out of bounds using set_cppo("fast") + io_context fix skipping len=0 + fix the typo in manual (dims -> dim) + add require(inline) to fix the problem with loading sysdata.rda

The post Stan 1.3.0 and RStan 1.3.0 Ready for Action appeared first on Statistical Modeling, Causal Inference, and Social Science.

To

**leave a comment**for the author, please follow the link and comment on their blog:**Statistical Modeling, Causal Inference, and Social Science » R**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...