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statespacer 0.5.0

Extra functionality

• Adds the option to generate forward simulations. See ?predict.statespacer for details.

Bug Fixes

• Fixes the returning of NA when calling Cholesky() without a format.

statespacer 0.4.1

Removed dependency

• Removes the dependency on the YieldCurve package by including an updated FedYieldCurve dataset in the statespacer package. See ?FedYieldCurve for details.

statespacer 0.4.0

Extra functionality

• Introduces the simulation smoother for drawing random samples conditional on the observed data. See ?SimSmoother for details.

Performance improvements

• Extraction of components now done a bit more efficiently.

Bug fixes

• Fixed incrementation of initialisation_steps during initialisation when the dependent variable was missing.

statespacer 0.3.0

Performance improvements

• Kalman Filter and Smoother now fully written in c++.

Extra functionality

• Computation of diagnostics now optional using diagnostics = TRUE.
• Added full system matrices to the statespacer object.
• Added predicted, filtered, and forecasted P_star and P_inf.

Bug fixes

• Fixed bug in predicting using explanatory variables.
• Fixed edge case in adding explanatory variables. The bug occurred when there was only 1 explanatory variable and 1 dependent variable supplied, causing the Z system matrix to be a vector instead of an array.

statespacer 0.2.1

Bug fixes

• Patch for macOS. On macOS, assignment of nested lists is handled a bit differently than on other platforms. For instance, if first <- list(), then assigning first$second[[["third"]] <- 1 returns on Windows (and other platforms) a list named first, that contains another list named second, that contains a named element third equal to an unnamed length 1 numerical vector. On macOS though, it returns a list named first, that contains a named element second equal to a named (third) length 1 numerical vector. So second is a list on the other platforms, while being a named numerical vector on macOS. This caused a bug on macOS while computing standard errors.

statespacer 0.2.0

Breaking changes

• API change by making use of S3 classes and methods:

  • Replaced StateSpaceFit() for statespacer().

  • Replaced StateSpaceEval(...) for statespacer(..., fit = FALSE).

  • statespacer() returns a list object of class statespacer.

  • Replaced StateSpaceForecast() for the S3 method predict.statespacer().

Performance improvements

• Major:

  • Calculation of loglikelihood now done using c++. Major performance improvement as the loglikelihood potentially gets calculated a lot of times by the optimisation procedure.

• Minor:

  • Making use of crossprod and tcrossprod.

  • Improved efficiency of the computation of standard_errors.

  • y_temp outside of LogLikelihood function.

  • Easier to find proper initial values, reducing time spent on trial and error by the user.

Extra functionality

• Printing progress now optional using verbose = TRUE.

• Computation of standard_errors now optional using standard_errors = TRUE.

statespacer 0.1.0

• Initial release to CRAN!

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.