News

bssm 0.1.7 (Release date: 2019-03-19)

• Fixed a bug in EKF smoother which resulted wrong smoothed state estimates in case of partially missing multivariate observations. Thanks for Santeri Karppinen for spotting the bug.
• Added twisted SMC based simulation smoothing algorithm for Gaussian models, as an alternative to Kalman smoother based simulation.

bssm 0.1.6-1 (Release date: 2018-11-20)

• Fixed wrong dimension declarations in pseudo-marginal MCMC and logLik methods for SDE and ng_ar1 models.
• Added a missing Jacobian for ng_bsm and bsm models using IS-correction.
• Changed internal parameterization of ng_bsm and bsm models from log(1+theta) to log(theta).

bssm 0.1.5 (Release date: 2018-05-23)

• Fixed the Cholesky decomposition in filtering recursions of multivariate models.
• as_gssm now works for multivariate Gaussian models of KFAS as well.
• Fixed several issues regarding partially missing observations in multivariate models.
• Added the MASS package to Suggests as it is used in some unit tests.
• Added missing type argument to SDE MCMC call with delayed acceptance.

bssm 0.1.4-1 (Release date: 2018-02-04)

• Fixed the use of uninitialized values in psi-filter from version 0.1.3.

bssm 0.1.4 (Release date: 2018-02-04)

• MCMC output can now be defined with argument type. Instead of returning joint posterior samples, run_mcmc can now return only marginal samples of theta, or summary statistics of the states.
• Due to the above change, argument sim_states was removed from the Gaussian MCMC methods.
• MCMC functions are now less memory intensive, especially with type="theta".

bssm 0.1.3 (Release date: 2018-01-07)

• Streamlined the output of the print method for MCMC results.
• Fixed major bugs in predict method which caused wrong values for the prediction intervals.
• Fixed some package dependencies.
• Sampling for standard deviation parameters of BSM and their non-Gaussian counterparts is now done in logarithmic scale for slightly increased efficiency.
• Added a new model class ar1 for univariate (possibly noisy) Gaussian AR(1) processes.
• MCMC output now includes posterior predictive distribution of states for one step ahead to the future.

bssm 0.1.2 (Release date: 2017-11-21)

• API change for run_mcmc: All MCMC methods are now under the argument method, instead of having separate arguments for delayed acceptance and IS schemes.
• summary method for MCMC output now omits the computation of SE and ESS in order to speed up the function.
• Added new model class lgg_ssm, which is a linear-Gaussian model defined directly via C++ like non-linear nlg_ssm models. This allows more flexible prior definitions and complex system matrix constructions.
• Added another new model class, sde_ssm, which is a model with continuous state dynamics defined as SDE. These too are defined via couple simple C++ functions.
• Added non-gaussian AR(1) model class.
• Added argument nsim for predict method, which allows multiple draws per MCMC iteration.
• The noise multiplier matrices H and R in nlg_ssm models can now depend on states.

bssm 0.1.1-1 (Release date: 2017-06-27)

• Use byte compiler.
• Skip tests relying in certain numerical precision on CRAN.

bssm 0.1.1 (Release date: 2017-06-27)

• Switched from C++11 PRNGs to sitmo.
• Fixed some portability issues in C++ codes.

bssm 0.1.0 (Release date: 2017-06-24)

• Initial release.

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