Bayesian Non- and Semi-parametric Method

Forfatter

Kort om boken

This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distribu…

Oppdag mer

Velg tagger...
Spar {0}
Spar {0} som ARK-VENN
{0} til nettpris
med Klikk&Hent
Format/språk
Format
Forklaring av formater
  • Innbundet

    Bok med hardt omslag.

  • Pocket

    Heftet bok med mykt omslag.

  • Kartonert

    Bok med tykke, stive sider.

  • E-Bok

    Digitalt format. E-bok kan leses i ARK-appen eller på Kindle. Bøkene kan også lastes ned fra Din side.

  • Nedlastbar lydbok

    Digitalt format. Nedlastbar lydbok kan lyttes til i ARK-appen. Bøkene kan også lastes ned fra Din side.

  • Digikort lydbok

    Lydbok på digikort. Krever Digispiller.

  • Compact Disc

    Lydbok eller musikk på CD. Krever CD-spiller eller annen kompatibel avspiller.

  • Vinyl

    Vinylplate. Krever platespiller.

  • DVD

    DVD-film. Krever DVD-spiller eller annen kompatibel avspiller.

  • Blu-ray

    Blu-ray-film. Krever Blu-ray-spiller eller annen kompatibel avspiller.

   Fri frakt - på kjøp over 249,-
   Alltid bytterett - Norges beste. Bytt uten kvittering.

    Om Bayesian Non- and Semi-parametric Method

    This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid " overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility. This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm, " which implements all of the non-parametric models discussed in the book.

    Kundevurderinger

    Totalvurdering: 

    Gi din vurdering: 
    Totalvurdering: 

    Detaljer

    Format
    E-Bok
    Kopisperre
    Teknisk DRM
    Filformat
    ePUB
    Utgivelsesår
    2014
    Forlag
    Princeton University Press
    Språk
    Engelsk
    ISBN
    9781400850303
    Sider
    224

    Anbefalt