legion v0.1.2 (Release data: 2023-01-30) ======= Changes: * The order in which in plot.legion() now matters. * Allow estimating seasonal vets() on the short data (one season of data). * auto.vets() now does not check for common initial level and common level component. This is not practical. Bugfixes: * Fixed a bug in dimnames for some vets() models. * ves() and vets() would produce an error in case of h=1 due to drop of one of the dimensions by R, when extracting the holdout. * Fix in auto.vets() for level models with no checks for initials and components. * measures() was not imported from greybox for some reason. Now it is. * Different initialisation of persistence matrix in ves(), so that it does not get stuck in the violation of stability condition. legion v0.1.1 (Release data: 2022-02-14) ======= Changes: * Usual bounds are now available in vets. This will make all parameters lie between 0 and 1. * Custom loss function for both ves() and vets(). * We now import forecast from generics package, not from greybox. * Correct names of states that include original names of time series in vets(). Bugfixes: * forecast.legion would not work correctly if variables did not have names. legion v0.1.0 (Release data: 2021-05-15) ======= Changes: * Imported ves() and vets() functions from smooth package. * We now have explicit lags parameter in ves() and vets(). * First working version of vets(). * architectorVETS in vets() - internal function needed for selector. * vets() and ves() now support model selection. * vets() now has a proper likelihood estimation and implementation of multiplicative error model. * ves() now also has a proper MLE. * Parameter "silent" can now only be TRUE or FALSE. * auto.vets() function, selecting PIC elements via I->P->C. * plot() method for ves() and vets(). Currently only produces plots 1 and 4-7. * Fixed BICc and AICc for multivariate models. * loss="diagonal" now refers to likelihood maximisation, assuming that the series are independent. * auto.vets() now starts with the model with loss="diagonal", implying that covariances are all zero. * Substituted the parameters "y" with "data". * A brief vignette for vets(). * plot.legion() method now supports all plots. * forecast.legion() and related methods is now available. * ves() and vets() now work with zoo classes of data. * on.exit() restore par for plot functions.