Separabilità di per spazi riflessivi, misura gaussiana
Following H. Sato - Y. Okazaky we will prove that: if is a topological vector space, locally convex and reflexive, and is a gaussian measure on , then is separable.
Following H. Sato - Y. Okazaky we will prove that: if is a topological vector space, locally convex and reflexive, and is a gaussian measure on , then is separable.
By using convolution, we will give a theorem about density of «usual» processes in the space of generalized stochastic processes. An integration theorem is given also. At last, some example.
In this paper the A. finds out necessary and sufficient conditions for the existence, or non existence, of a minimal sufficient statistics between general probability spaces. The method used here comes out from the study of the relations, in the range, between sufficient statistics and from the study of the -algebras induced by them.
Following H. Sato - Y. Okazaky we will prove that: if is a topological vector space, locally convex and reflexive, and is a gaussian measure on , then is separable.
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