Compositional combination and selection of forecasters
The Split-Then-Combine approach has previously been used to generate the weights of forecasts in a combination in the Euclidean space. This paper extends this approach to combine forecasts inside the simplex space, the sample space of positive weights adding up to one. As it turns out, the simplicia...
| Autores: | , |
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| Formato: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Recursos: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/712483 |
| Acesso em linha: | http://hdl.handle.net/10486/712483 https://dx.doi.org/10.2436/20.8080.02.123 |
| Access Level: | acceso abierto |
| Palavra-chave: | Aitchison geometry Combination-After-Selection Dimensionality problem Simplex Split-Then-Combine Economía |
| Resumo: | The Split-Then-Combine approach has previously been used to generate the weights of forecasts in a combination in the Euclidean space. This paper extends this approach to combine forecasts inside the simplex space, the sample space of positive weights adding up to one. As it turns out, the simplicial statistic given by the sample centre compares favourably against the fxed-weight, average forecast. Besides, we also develop a Combination-After-Selection method to get rid of redundant forecasters. We apply these approaches to make out-of-sample one-step ahead combinations and subcombinations of forecasts for several economic variables. This methodology is particularly useful when the sample size is smaller than the number of forecasts, a case where other methods (e.g., ordinary least squares or principal component analysis) are not applicable |
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