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In this paper methods are presented for obtaining parametric measures of information from the non-parametric ones and from information matrices. The properties of these measures are examined. The one-dimensional parametric measures which are derived from the non-parametric are superior to Fisher's information measure because they are free from regularity conditions. But if we impose the regularity conditions of the Fisherian theory of information, these measures become linear functions of Fisher's measure.doi:10.1016/s0019-9958(81)90263-1 fatcat:i5d3acredzdotptdhp46pjpe4m