scholarly journals Efficient Parameter Estimation of Generalizable Coarse-Grained Protein Force Fields Using Contrastive Divergence: A Maximum Likelihood Approach

2013 ◽  
Vol 9 (12) ◽  
pp. 5718-5733 ◽  
Author(s):  
Csilla Várnai ◽  
Nikolas S. Burkoff ◽  
David L. Wild
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Force Fields ◽  
Coarse Grained ◽  
Maximum Likelihood Approach ◽  
Contrastive Divergence ◽  
Likelihood Approach ◽  
Protein Force Fields

scholarly journals Flexible Birnbaum–Saunders Distribution

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1305 ◽  
Author(s):  
Guillermo Martínez-Flórez ◽  
Inmaculada Barranco-Chamorro ◽  
Heleno Bolfarine ◽  
Héctor W. Gómez
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Environmental Sciences ◽  
Maximum Likelihood Approach ◽  
Special Cases ◽  
Competing Models ◽  
Likelihood Approach ◽  
Iterative Maximum Likelihood ◽  
Extra Parameter ◽  
Better Than

In this paper, we propose a bimodal extension of the Birnbaum–Saunders model by including an extra parameter. This new model is termed flexible Birnbaum–Saunders (FBS) and includes the ordinary Birnbaum–Saunders (BS) and the skew Birnbaum–Saunders (SBS) model as special cases. Its properties are studied. Parameter estimation is considered via an iterative maximum likelihood approach. Two real applications, of interest in environmental sciences, are included, which reveal that our proposal can perform better than other competing models.

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