Changelog

Source: NEWS.md

statespacer 0.5.0

Extra functionality

Bug Fixes

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

statespacer 0.4.12022-05-10

Removed dependency

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

statespacer 0.4.02020-11-19

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 0.3.02020-09-15

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 0.2.12020-07-15

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 0.2.02020-07-13

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 0.1.02020-05-16

  • Initial release to CRAN!