Logconcavity versus logconvexity: a complete characterization.

The writer presents a complete characterization of logconcavity, which is an increasingly popular concept in the economics of uncertainty and information. He points out that a random variable or a random vector is logconcavely distributed if the logarithm of its probability density function is conc...

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Publicado en:Journal of Economic Theory Vol. 80; no. 2; pp. 350 - 370
Autor principal: An, Mark Yuying
Formato: Artículo
Publicado: Academic Press Inc. June 1998
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: June 1998
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      pub: Academic Press Inc.
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        512661682
        10.1006/jeth.1998.2400
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        atl: Logconcavity versus logconvexity: a complete characterization.
      aug:
        au: An, Mark Yuying
      su:
        Logarithms
        Uncertainty
        Economics
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        subj:
          Logarithms
          Uncertainty
          Economics
      ab: The writer presents a complete characterization of logconcavity, which is an increasingly popular concept in the economics of uncertainty and information. He points out that a random variable or a random vector is logconcavely distributed if the logarithm of its probability density function is concave. He proves new and known results without the assumption that density functions are differentiable. He undertakes a systematic comparison between logconcavity and logconvexity and explores the source of the asymmetries between the two. He points out that the key difference is that logconcavity is preserved under one-sided integrations regardless of the types of distribution supports. He notes that this property does not hold for logconvexity. In addition, he considers logconcavity for multivariate distributions.
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    language: English
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