Faria, Alvaro and Mubwandarikwa, Emmanuel
(2008).
*International Journal of Statistics and Management Systems*, 3(1-2) pp. 1–25.

URL: | http://www.math.binghamton.edu/arcones/ijsms/volum... |
---|---|

Google Scholar: | Look up in Google Scholar |

## Abstract

We propose the geometric combination of predictive probability density functions as an alternative approach to the usually adopted linear combination. We show the conditions under which the geometric combination of Student t-densities is unimodal. Also, unlike the linear methods, geometric combinations are of closed form for densities from the regular exponential family and thus unimodal. A comparative analysis of linear and geometric combinations of predictive Student t{densities from regression dynamic linear models in a case of beverage sales forecasting in Zimbabwe shows the geometric method consistently producing skewed but unimodal densities. Consequences of decisions associated with both symmetric (quadratic and exponential) and non{symmetric (logarithmic) loss functions are investigated for multimodal linear combination densities when di®erent location parameters (means and largest modes) are chosen as point estimates. [brace not closed]

Item Type: | Journal Article |
---|---|

ISSN: | 0973-7395 |

Academic Unit/Department: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics Faculty of Science, Technology, Engineering and Mathematics (STEM) |

Item ID: | 12328 |

Depositing User: | Àlvaro Faria |

Date Deposited: | 17 Nov 2008 13:29 |

Last Modified: | 04 Oct 2016 10:15 |

URI: | http://oro.open.ac.uk/id/eprint/12328 |

Share this page: |