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SAIG
2000
Springer

Generating Data Analysis Programs from Statistical Models

8 years 10 months ago
Generating Data Analysis Programs from Statistical Models
Extracting information from data, often also called data analysis, is an important scienti c task. Statistical approaches, which use methods from probability theory and numerical analysis, are wellfounded but di cult to implement: the development of a statistical data analysis program for any given application is time-consuming and requires knowledge and experience in several areas. In this paper, we describe AutoBayes, a high-level generator system for data analysis programs from statistical models. A statistical model speci es the properties for each problem variable i.e., observation or parameter and its dependencies in the form of a probability distribution. It is thus a fully declarative problem description, similar in spirit to a set of di erential equations. From this model, AutoBayes generates optimized and fully commented C C++ code which can be linked dynamically into the Matlab and Octave environments. Code is generated by schema-guided deductive synthesis. A schema consists...
Bernd Fischer 0002, Johann Schumann, Thomas Pressb
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where SAIG
Authors Bernd Fischer 0002, Johann Schumann, Thomas Pressburger
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