fDMA ver. 2.2.7 (Release date: 2023-07-15) ============== Changes: * Small typo correction in tvpcpp() made. * Minor issues with CRAN policies detected and fixed. fDMA ver. 2.2.6 (Release date: 2020-07-16) ============== Changes: * altf() and altf2() corrected to consider out-of-sample forecasts. * Markov Switching Models dropped from altf(). * Vignette changed. fDMA ver. 2.2.5 (Release date: 2020-04-03) ============== Changes: * Guarantee of positive-definiteness after updating fixed in tvpcpp(). * Small syntax corrections. fDMA ver. 2.2.4 (Release date: 2018-09-29) ============== Changes: * Changes to follow STRICT_R_HEADERS via Rcpp made. * Small corrections in computations of coefficients in tvp() and tvpcpp() made. * Forecast computation of DMA-E in Dynamic Occam's Window method corrected. * Adding a small constant to posterior model probabilities fixed. * Setting initial values of variances fixed. * Google probabilities computations fixed and allowed to cover only selected period. * Small changes in fDMA() to increase the speed of computations made. * Option to specify the number of cores used in parallel version of fDMA() added. * Alternative averaging schemes added to fDMA(). * forced.models, forbidden.models and forced.variables arguments added to fDMA(). * reduce.size() added. * coef(), fitted(), predict(), residuals() and rvi() for "dma" object added. * Non-interactive option to plot methods added. * Small changes to improve the performance added. fDMA ver. 2.2.3.1 (Release date: 2018-06-29) ============== Changes: * Small correction in NAMESPACE fDMA ver. 2.2.3 (Release date: 2018-01-28) ============== Changes: * Vignette added. * Possible zero posterior model probabilities corrected in fDMA() and altf4(). fDMA ver. 2.2.2 (Release date: 2018-01-21) ============== Changes: * Exponentially weighted moving average variance updating corrected. fDMA ver. 2.2.1 (Release date: 2017-11-24) ============== Changes: * Warnings of replacing previous imports between Rcpp and utils corrected. fDMA ver. 2.2 (Release date: 2017-11-15) ============== Changes: * Crucial part, i.e., tvp(), rewritten in C++ to increase the speed of computations. fDMA ver. 2.1 (Release date: 2017-10-12) ============== Changes: * Dynamic Occam's Window extended to work even if not all possible models with a constant are used. * Limit of number of models used by Dynamic Occam's Window added. * Option to print during computations with Dynamic Occam's Window the number of currently computed recursive DMA round and the number of models used in this round added. * grid.DMA() fixed to work with multiple lambda values. * Google probabilities computations fixed. * NA coefficients in altf() and altf2() fixed. * Problem with constant x fixed in tvp(). * Plotting posterior model probabilities in plot.dma() fixed. * Akaike Information Criterion with a correction for finite sample sizes (AICc) added to rec.reg(), roll.reg(), altf2() and altf3(). * Google probabilities added to altf2(). * altf3() and altf4() fixed to work with models with constant only. * Relative variable importance and expected number of variables added to altf2() and plot.altf2(). * More outcomes summary added to summary.altf2(). * Expected window size added to altf3(), altf4(), plot.altf3() and plot.altf4(). * descstat() for basic descriptive statistics added. * standardize() added to rescale variables to have mean 0 and standard deviation 1. * onevar() added to quickly create a matrix indicating one-variable models. * archtest() outcomes changed to "htest" class. fDMA ver. 2.0 (Release date: 2017-08-31) ============== Changes: * Engle's ARCH test added. * Forecast accuracy tests added. * A few stationarity tests added. * grid.roll.reg() (as "grid.roll.reg" object) for roll.reg() with various windows added. * rec.reg() for recursive regression added. * roll.reg() outcomes as an object of "reg" class. * Akaike Information Criterion, Bayesian Information Criterion and Mean Squared Error added to roll.reg() outcomes. * Regression coefficients and p-values for t-test for regression coefficients added to roll.reg() outcomes. * roll.reg() fixed to work also with constant only. * grid.tvp() (as "grid.tvp" object) for tvp() with various lambdas added. * Predicitive density and estimated regression coefficients from all periods added to tvp() outcomes. * Exponentially weighted moving average variance updating added to tvp(). * tvp() changed in order to work inside fDMA(), outcomes as "tvp" class. * altf4() for averaging over different windows sizes for a time-varying parameters rolling regression added. * altf3() for averaging over different windows sizes for a rolling regression added. * alft2() for model averaging alternative forecast added. * More outcomes added to altf(). * Direct comparision of a "dma" class object with alternative forecast added to altf(). * Option to choose which alternative forecast will be computed by altf() added. * For forecast quality measure Mean Squared Error replaced by Root Mean Squared Error. * Number of models used in Dynamic Occam's Window method and posterior model probabilities added to plot(). * "inc" display in summary() of fDMA() outcomes fixed. * Predicitive densities from the last period added to fDMA() outcomes. * fDMA() upgraded to work better with parallel computations on Windows machines. * Setting the initial values of variance for the models equations in fDMA() fixed. * Estimation of models without constant fixed. fDMA ver. 1.1 (Release date: 2017-07-11) ============== Changes: * Plot's menu fixed. fDMA ver. 1.0 (Release date: 2017-07-09) ============== * Initial release.