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How to use or fill out On a Multiplicative Algorithm for Computing Bayesian
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Click ‘Get Form’ to open it in the editor.
Begin by reviewing the introduction section, which outlines the purpose of the multiplicative algorithm and its relevance to Bayesian D-optimal designs.
Fill in your parameters of interest in the designated fields, ensuring that you understand how they relate to the Fisher information matrix.
Utilize the iterative algorithm section to input your initial design weights. Follow the guidelines provided for setting convergence criteria.
Incorporate any necessary adjustments based on the nearest neighbor exchange strategy mentioned, which can enhance algorithm speed.
Review your entries for accuracy before finalizing. Ensure all required fields are completed as per the document's specifications.
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Related links
On a Multiplicative Algorithm for Computing Bayesian D
by Y Yu 2010 Cited by 3 We use the minorization-maximization principle (Lange, Hunter and Yang 2000) to establish the monotonicity of a multiplicative algorithm for computing Bayesian
by C Leuenberger 2010 Cited by 221 The situation changed with the advent of likelihood-free inference algorithms, often subsumed under the term approximate Bayesian computation (ABC).
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