April 12, 2013
Stan 1.3.0 and RStan 1.3.0 Ready for Action
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)
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Enhancements
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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
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* 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