TY  - JOUR
TI  - A predictable outcome
EP  - 13
AV  - public
Y1  - 2015/04//
ID  - discovery1470383
N2  - Gianluca Baio and Roberto Cerina used a modified version of a dynamic Bayesian forecasting model to "predict" the 2014 US Senate elections. The results bode well for the 2016 vote.
PB  - Blackwell Publishing Ltd
N1  - This is the peer reviewed version of the following article: Baio, G. and Cerina, R. (2015), A predictable outcome. Significance, 12: 11?13., which has been published in final form at doi: 10.1111/j.1740-9713.2015.00810.x. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
IS  - 2
VL  - 12
SP  - 11
JF  - Significance
A1  - Baio, G
A1  - Cerina, R
SN  - 1740-9713
UR  - http://dx.doi.org/10.1111/j.1740-9713.2015.00810.x
ER  -