Provides eigenvector-based (geometric) forecast combination methods; also includes simple approaches (simple average, median, trimmed and winsorized mean, inverse rank method) and regression-based combination. Tools for data pre-processing are available in order to deal with common problems in forecast combination (missingness, collinearity).
|Author||Christoph E. Weiss, Gernot R. Roetzer|
|Date of publication||2016-11-27 16:02:26|
|Maintainer||Christoph E. Weiss <email@example.com>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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