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How regressive objective regression methodology finds information beyond a white noise

Author: 
Ricardo Osés Rodríguez, Jaime Wilfrido Aldaz Cárdenas, Rigoberto Fimia Duarte, Jorge Jagger Segura Ochoa, Iosbel Burgos Alemán, Claudia Osés Llanes, Nancy Guadalupe Aldaz Cárdenas, Jenny Janeth Segura Ochoa, Danilo Fabián Yánez Silva, Víctor Danilo Mon
Abstract: 

The objective of this paper is to determine how methodology ROR can give information when having a series, whose auto correlograms are a white noise. Deceased by car accidents variable was used for Cuba in the period 2006- 2011. The future projection of the data series can be obtained by using modeling ROR, which provides a new and important way, promising for the series that behave as a white noise, because this gives new information for the series and its behavior. Deceased tendency is to diminish at about 29 persons a year; deceased persons depend on quantity of deceased two years backwards. As the model is perfect and errors with zero value are obtained, Cristosols Numbers are introduced, which could create new statistics and prediction models. This study was done using the statistical package of Social Sciences (SPSS) Version 13.

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