Sufficiency and Approximate Sufficiency

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

K2-ABC: Approximate Bayesian Computation with Infinite Dimensional Summary Statistics via Kernel Embeddings (2015, methodology): “Experiments on a simulated scenario and a real-world biological problem illustrate the effectiveness of the proposed algorithm.”
Information, Divergence and Risk for Binary Experiments (2009, methodology): “…of non-standard analysis (Nelson, 1987; Lutz and Musio, 2005) as the foundations for probability; Topsøe’s (Topsøe, 2006), Shafer and Vovk’s (Shafer and Vovk, 2001) game theory as a basis, and Le Cam’s use of Riesz measures on a vector lattice to replace the traditional sample space (LeCam, 1964).”
Statistical Applications in Genetics and Molecular Biology Approximately Sufficient Statistics and Bayesian Computation (2011, background): “These issues are related to the concept of “nearly sufficient” statistics (Le Cam, 1964; Abril, 1994; Cabrera and Yohai, 1999).”
On the measure of the information in a statistical experiment (2007, methodology): “This paper makes that framework explicit by building on the sufficiency ordering of experiments considered in Blackwell (1951, 1953) and Le Cam (1964, 1986).”