Stan 2.7 (CRAN, variational inference, and much much more)

July 22, 2015

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


Stan 2.7 is now available for all interfaces. As usual, everything you need can be found starting from the Stan home page:


  • RStan is on CRAN!(1)
  • Variational Inference in CmdStan!!(2)
  • Two new Stan developers!!! 
  • A whole new logo!!!! 
  • Math library with autodiff now available in its own repo!!!!! 

(1) Just doing install.packages(“rstan”) isn’t going to work because of dependencies; please go to the RStan getting started page for instructions of how to install from CRAN. It’s much faster than building from source and you no longer need a machine with a lot of RAM to install.

(2) Coming soon to an interface near you.

Full Release Notes

v2.7.0 (9 July 2015)

New Team Members
* Alp Kucukelbir, who brings you variational inference
* Robert L. Grant, who brings you the StataStan interface

Major New Feature
* Black-box variational inference, mean field and full
  rank (#1505)

New Features
* Line numbers reported for runtime errors (#1195)
* Wiener first passage time density (#765) (thanks to
  Michael Schvartsman)
* Partial initialization (#1069)
* NegBinomial2 RNG (#1471) and PoissonLog RNG (#1458) and extended
  range for Dirichlet RNG (#1474) and fixed Poisson RNG for older
  Mac compilers (#1472)
* Error messages now use operator notation (#1401)
* More specific error messages for illegal assignments (#1100)
* More specific error messages for illegal sampling statement 
  signatures (#1425)
* Extended range on ibeta derivatives with wide impact on CDFs (#1426)
* Display initialization error messages (#1403)
* Works with Intel compilers and GCC 4.4 (#1506, #1514, #1519)

Bug Fixes
* Allow functions ending in _lp to call functions ending in _lp (#1500)
* Update warnings to catch uses of illegal sampling functions like
  CDFs and updated declared signatures (#1152)
* Disallow constraints on local variables (#1295)
* Allow min() and max() in variable declaration bounds and remove
  unnecessary use of math.h and top-level :: namespace (#1436)
* Updated exponential lower bound check (#1179)
* Extended sum to work with zero size arrays (#1443)
* Positive definiteness checks fixed (were > 1e-8, now > 0) (#1386)

Code Reorganization and Back End Upgrades
* New static constants (#469, #765)
* Added major/minor/patch versions as properties (#1383)
* Pulled all math-like functionality into stan::math namespace
* Pulled the Stan Math Library out into its own repository (#1520)
* Included in Stan C++ repository as submodule
* Removed final usage of std::cout and std::cerr (#699) and
  updated tests for null streams (#1239)
* Removed over 1000 CppLint warnings
* Remove model write CSV methods (#445)
* Reduced generality of operators in fvar (#1198)
* Removed folder-level includes due to order issues (part of Math
  reorg) and include math.hpp include (#1438)
* Updated to Boost 1.58 (#1457)
* Travis continuous integration for Linux (#607)
* Add grad() method to math::var for autodiff to encapsulate math::vari
* Added finite diff functionals for testing (#1271)
* More configurable distribution unit tests (#1268)
* Clean up directory-level includes (#1511)
* Removed all lint from new math lib and add cpplint to build lib
* Split out derivative functionals (#1389)

Manual and Documentation
* New Logo in Manual; remove old logos (#1023)
* Corrected all known bug reports and typos; details in 
  issues #1420, #1508, #1496
* Thanks to Sunil Nandihalli, Andy Choi, Sebastian Weber,
  Heraa Hu, @jonathan-g (GitHub handle), M. B. Joseph, Damjan
  Vukcevic, @tosh1ki (GitHub handle), Juan S. Casallas
* Fix some parsing issues for index (#1498)
* Added chapter on variational inference
* Added strangely unrelated regressions and multivariate probit
* Discussion from Ben Goodrich about reject() and sampling
* Start to reorganize code with fast examples first, then
* Added file (#1408)

The post Stan 2.7 (CRAN, variational inference, and much much more) appeared first on Statistical Modeling, Causal Inference, and Social Science.

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