TY  - JOUR
ID  - eprints1640
EP  - 23
AV  - none
TI  - Ordinary Least Squares and Genetic Algorithms Optimization in Smoothing Transition Autoregressive (STAR) Models
KW  - Genetic Algorithms; MATLAB; Membership Functions; Smoothing Transition Autoregressive
UR  - http://www.svpublishers.co.uk/#/ijcis-mar-2011/4550826231
SN  - 2229-5208
N2  - Abstract?In this paper we present, propose and examine
additional membership functions as also we propose least squares with genetic algorithms optimization in order to find the optimum fuzzy membership functions parameters. More
specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. The reason we propose that is because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach therefore more functions should be tested. Some numerical applications for S&P 500, FTSE 100 stock returns and for unemployment rate are presented and MATLAB routines are provided
VL  - 2
Y1  - 2011/03//
IS  - 3
JF  - International Journal of Computer Information Systems
A1  - Giovanis, Eleftherios
PB  - Silicon Valley Publishers
SP  - 17
ER  -