FoReco 0.2.0

Major changes

• It's possible to use a subset of factors of m (max. order of temporal aggregation);
• Added the possibility for htsrec(), thfrec() and octrec() to introduce a list of h covariance matrices in the parameters W and Omega, where h stands for the forecast horizon (note that for thfrec() and octrec() this is the forecast horizon of the entire cycle);
• Param Sstruc is no more avaible in octrec() and ctf_tools(). FoReco uses a fast algorithm to compute Scheck, so no external input is needed;
• Modified output of ctf_tools() (added Ccheck, Htcheck, Scheck, removed Cstruc, Sstruc), hts_tools() (added C) and thf_tools() (added m);
• Added two new not negative reconciliation techniques ("KAnn" and "sntz") with a new parameter (nn_type) in htsrec(), thfrec() and octrec();
• Added the top-down reconciliation function tdrec();
• Added the level conditional forecast reconciliation (with and without not-negative constraints) for genuine hierarchical/grouped time series levrec() (cross-sectional, temporal and cross-temporal).

Minor changes

• Now in octrec() it is also possible to introduce the Ω covariance matrix variant through the Omega parameter and not only the W variant with the W parameter;
• Updated tcsrec(), cstrec() and iterec(). In the iterec function the maxit parameter has been replaced by itmax, however for the moment maxit is still supported;
• Now FoReco removes null rows from the cross-sectional aggregation matrix C and it warns the user if the balanced version of an unbalanced hierarchy is considering duplicated variables;
• Redesigned the console output and added a new convergence norm as default for iterec() (norm parameter).

Experimental

• Add the possibility to introduce constraints through the bounds param in htsrec(), thfrec() and octrec();
• Add a function oct_bounds() to organize the bounds on a specific dimension (i.e. only cross-sectional or only temporal) in a cross-temporal framework;
• Added ut2c() and srref() to develop a cross-sectional structural representation starting from a zero constraints kernel matrix;
• Added in score_index() the calculation of multiple forecast horizons index (like 1:6) and multiple cross-sectional levels for a forecasting experiment.