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Mach Learn (2010) 79: 261 282 DOI 10.1007/s10994-009-5144-4 A multivariate Bayesian scan statistic for early event detection and characterization Daniel B. Neill Gregory F. Cooper Received: 27 November
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What is a multivariate bayesian scan?
A multivariate bayesian scan is a statistical analysis technique that uses Bayesian inference to analyze and model the relationships between multiple variables in a dataset.
Who is required to file a multivariate bayesian scan?
There is no specific requirement for individuals or entities to file a multivariate bayesian scan. It is a statistical analysis technique that can be used by researchers and analysts to analyze data.
How to fill out a multivariate bayesian scan?
To fill out a multivariate bayesian scan, you would typically need to have a dataset with multiple variables and apply Bayesian inference techniques to analyze the relationships between these variables. This can be done using software or programming languages that support Bayesian analysis.
What is the purpose of a multivariate bayesian scan?
The purpose of a multivariate bayesian scan is to gain insights into the relationships between multiple variables in a dataset. It can help identify patterns, associations, and dependencies among variables, and can be used for prediction and modeling purposes.
What information must be reported on a multivariate bayesian scan?
The information reported on a multivariate bayesian scan would depend on the specific analysis being conducted and the variables involved. Generally, the analysis would report on the estimated parameters, the strength of associations between variables, and any uncertainties or assumptions made during the analysis.
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