Declarative Statistics
This work provides a new framework for statisticians to tackle common problems, but it appears incremental as it builds on existing declarative modeling concepts.
The authors introduced declarative statistics, a suite of declarative modeling tools for statistical analysis, and deployed these tools to a wide range of application areas in classical statistics, contrasting the framework against established practices.
In this work we introduce declarative statistics, a suite of declarative modelling tools for statistical analysis. Statistical constraints represent the key building block of declarative statistics. First, we introduce a range of relevant counting and matrix constraints and associated decompositions, some of which novel, that are instrumental in the design of statistical constraints. Second, we introduce a selection of novel statistical constraints and associated decompositions, which constitute a self-contained toolbox that can be used to tackle a wide range of problems typically encountered by statisticians. Finally, we deploy these statistical constraints to a wide range of application areas drawn from classical statistics and we contrast our framework against established practices.