Stan 1.3.0 and RStan 1.3.0 Ready for Action

April 12, 2013

(This article was first published on Statistical Modeling, Causal Inference, and Social Science » R, and kindly contributed to R-bloggers)

Stan LogoThe 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:

Please let us know if you have problems updating.

Here’s the full set of release notes.

v1.3.0 (12 April 2013)

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    

* 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

* added method as.mcmc.list()
* compatibility with R 3.0.0

* 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

* additions to user's guide w. sample models
    + stochastic volatility example with source, optimized source, 
    + 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

* 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.

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