scholarly journals Correction to: Publication of Decision Model Source Code: Attitudes of Health Economics Authors

2019 ◽  
Vol 37 (11) ◽  
pp. 1411-1411
Author(s):  
Joanna Emerson ◽  
Rachel Bacon ◽  
Alma Kent ◽  
Peter J. Neumann ◽  
Joshua T. Cohen
2019 ◽  
Vol 37 (11) ◽  
pp. 1409-1410 ◽  
Author(s):  
Joanna Emerson ◽  
Rachel Bacon ◽  
Alma Kent ◽  
Peter J. Neumann ◽  
Joshua T. Cohen

The unique IDs that firms assign to all important models typically appear in just three places: model documents, validation documents, and model inventory databases. Where the IDs do not, as a rule, appear is within the actual model source code. Incomplete model inventory information (including usage) is a chronic issue throughout the financial industry. Few firms can accurately answer such vexing questions as how many times each model in inventory was executed during the last year, which models exhibit significant seasonality, which models are used in each geographic region or legal entity, or whether any unvalidated models were used during the last year on any firm computer. This article will demonstrate that a root cause of model usage opacity is, unfortunately, that most models do not actually know who they are. This article will further explain how software-embedded model IDs can be leveraged to increase transparency and address some of the most difficult questions that may be posed about model usage.


2021 ◽  
Author(s):  
soumya banerjee

Bayesian models are very important in modern data science. These models can be used to derive estimatesfor noisy and sparse data. This manuscript outlines the basics and derivations of a Bayesian linearregression model. Source code for performing Bayesian linear regression is also provided. I hope thisresource will enable broader understanding of the basics of Bayesian models.


1974 ◽  
Author(s):  
Graham J. Burkheimer ◽  
William E. Stein ◽  
Amnon Rapoport
Keyword(s):  

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