Schena Pietro (7 results)

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  • Language: Italian

    Published by , Schena Editore, 1985

    8875140235 / 9788875140236

    • Softcover

    Seller: librisaggi, SAN VITO ROMANO, Italylibrisaggi

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    brossura Copertina flessibile. Condition: Poor. Copertina flessibile con alette informative, sporca e scolorita; Dorso sporco; Sguardia con dedica autori; Pagine ingiallite. Copertina flessibile 648 8875140235 Mediocre (Poor) . Book.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2011

    3844331549 / 9783844331547

    • Softcover

    Seller: preigu, Osnabrück, Germanypreigu

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    Taschenbuch. Condition: Neu. Model Choice or Hypotheses Testing? | A discussion from a Bayesian point of view with application in Matlab | Pietro Schena | Taschenbuch | 100 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844331547 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2011

    3844331549 / 9783844331547

    • Softcover

    Seller: Mispah books, Redhill, SURRE, United KingdomMispah books

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    Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Language: English

    Published by LAP LAMBERT Academic Publishing Mai 2011, 2011

    3844331549 / 9783844331547

    • Softcover
    • Print on Demand

    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book points the attention on a very crucial topic in Statistics - Model Selection - from a Bayesian point of view. In particular we are interested in analyzing the way in which we have to think and rationalize, when dealing with a problem of model choice. In the Classical background, this problem is strictly related to the field of hypotheses testing, since most of the tools used by Classical statisticians, to support such type of decision, are tests over parameters in the model or likelihood ratios. In spite of this, Bayesian theory allows us to tackle this problem in a more general setting that does not necessarily coincide with the hypotheses testing approach, leading us to the point that a threshold between these two settings is needed. However it is not clear yet where the hypotheses testing ends, and the model selection begins. A possible key to the solution of this matter lies on the definition of a statistical model, and more specifically of a nested model. A model selection problem with nested models identified by inequality constraints will be considered to illustrate this idea, with the support of an application implemented with Matlab. 100 pp. Englisch.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2011

    3844331549 / 9783844331547

    • Softcover
    • Print on Demand

    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Schena PietroBorn in Monopoli (BA, Italy) in 1984, graduated cum laude from the Master of Science Economics and Social Sciences (2009) in Bocconi School of Management and Economics. Fields of interest and research: Decision analys.

  • Language: English

    Published by LAP LAMBERT Academic Publishing Mai 2011, 2011

    3844331549 / 9783844331547

    • Softcover
    • Print on Demand

    Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book points the attention on a very crucial topic in Statistics - Model Selection - from a Bayesian point of view. In particular we are interested in analyzing the way in which we have to think and rationalize, when dealing with a problem of model choice. In the Classical background, this problem is strictly related to the field of hypotheses testing, since most of the tools used by Classical statisticians, to support such type of decision, are tests over parameters in the model or likelihood ratios. In spite of this, Bayesian theory allows us to tackle this problem in a more general setting that does not necessarily coincide with the hypotheses testing approach, leading us to the point that a threshold between these two settings is needed. However it is not clear yet where the hypotheses testing ends, and the model selection begins. A possible key to the solution of this matter lies on the definition of a statistical model, and more specifically of a nested model. A model selection problem with nested models identified by inequality constraints will be considered to illustrate this idea, with the support of an application implemented with Matlab.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2011

    3844331549 / 9783844331547

    • Softcover
    • Print on Demand

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book points the attention on a very crucial topic in Statistics - Model Selection - from a Bayesian point of view. In particular we are interested in analyzing the way in which we have to think and rationalize, when dealing with a problem of model choice. In the Classical background, this problem is strictly related to the field of hypotheses testing, since most of the tools used by Classical statisticians, to support such type of decision, are tests over parameters in the model or likelihood ratios. In spite of this, Bayesian theory allows us to tackle this problem in a more general setting that does not necessarily coincide with the hypotheses testing approach, leading us to the point that a threshold between these two settings is needed. However it is not clear yet where the hypotheses testing ends, and the model selection begins. A possible key to the solution of this matter lies on the definition of a statistical model, and more specifically of a nested model. A model selection problem with nested models identified by inequality constraints will be considered to illustrate this idea, with the support of an application implemented with Matlab.