
We introduce the notion of a C k -diffeological statistical model, which allows us to apply the theory of diffeological spaces to (possibly singular) statistical models. In particular, we introduce a class of almost 2-integrable C k -diffeological statistical models that encompasses all known statistical models for which the Fisher metric is defined. This class contains a statistical model which does not appear in the Ay–Jost–Lê–Schwachhöfer theory of parametrized measure models. Then, we show that, for any positive integer k , the class of almost 2-integrable C k -diffeological statistical models is preserved under probabilistic mappings. Furthermore, the monotonicity theorem for the Fisher metric also holds for this class. As a consequence, the Fisher metric on an almost 2-integrable C k -diffeological statistical model P ⊂ P ( X ) is preserved under any probabilistic mapping T : X ⇝ Y that is sufficient w.r.t. P. Finally, we extend the Cramér–Rao inequality to the class of 2-integrable C k -diffeological statistical models.
probabilistic mapping, statistical model, Probability (math.PR), Mathematics - Statistics Theory, Statistics Theory (math.ST), 62B-05, 62F-10, diffeology, Cramér-Rao inequality, QA1-939, FOS: Mathematics, the Fisher metric, the fisher metric, Mathematics, Mathematics - Probability, cramér-rao inequality
probabilistic mapping, statistical model, Probability (math.PR), Mathematics - Statistics Theory, Statistics Theory (math.ST), 62B-05, 62F-10, diffeology, Cramér-Rao inequality, QA1-939, FOS: Mathematics, the Fisher metric, the fisher metric, Mathematics, Mathematics - Probability, cramér-rao inequality
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