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!