Recursive algorithms for unbalanced banded Toeplitz systems

2009 ◽  
Vol 16 (7) ◽  
pp. 561-587 ◽  
Author(s):  
P. Favati ◽  
G. Lotti ◽  
O. Menchi
Keyword(s):  
Recursive Algorithms ◽  
Toeplitz Systems

scholarly journals Recursive algorithms for the computation of the potential harmonic coefficients of a constant density polyhedron

2009 ◽  
Vol 83 (10) ◽  
pp. 925-942 ◽  
Author(s):  
Dimitrios Tsoulis ◽  
Olivier Jamet ◽  
Jérôme Verdun ◽  
Nicolas Gonindard
Keyword(s):  
Constant Density ◽  
Recursive Algorithms ◽  
Potential Harmonic

scholarly journals APPLICATION OF AN ADAPTIVE STEP-SIZE ALGORITHM IN MODELS OF HYPERINFLATION

2012 ◽  
Vol 16 (S3) ◽  
pp. 355-375 ◽  
Author(s):  
Olena Kostyshyna
Keyword(s):  
New York ◽  
Mean Squared Error ◽  
American Economic Review ◽  
Sufficient Information ◽  
Recursive Algorithms ◽  
Time Varying ◽  
Step Size ◽  
Adaptive Step Size ◽  
Squared Error ◽  
Adaptive Step

An adaptive step-size algorithm [Kushner and Yin,Stochastic Approximation and Recursive Algorithms and Applications, 2nd ed., New York: Springer-Verlag (2003)] is used to model time-varying learning, and its performance is illustrated in the environment of Marcet and Nicolini [American Economic Review93 (2003), 1476–1498]. The resulting model gives qualitatively similar results to those of Marcet and Nicolini, and performs quantitatively somewhat better, based on the criterion of mean squared error. The model generates increasing gain during hyperinflations and decreasing gain after hyperinflations end, which matches findings in the data. An agent using this model behaves cautiously when faced with sudden changes in policy, and is able to recognize a regime change after acquiring sufficient information.

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