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Empirico-Statistical Analysis of Narrative Material and its Applications to Historical Dating: Volume I: The Development of the Statistical Tools - Couverture souple

 
9789401714129: Empirico-Statistical Analysis of Narrative Material and its Applications to Historical Dating: Volume I: The Development of the Statistical Tools
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  • ÉditeurSpringer
  • Date d'édition2014
  • ISBN 10 9401714126
  • ISBN 13 9789401714129
  • ReliureBroché
  • Nombre de pages240
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Autres éditions populaires du même titre

9780792326045: Empirico-Statistical Analysis of Narrative Material and Its Applications to Historical Dating: The Development of the Statistical Tools

Edition présentée

ISBN 10 :  0792326040 ISBN 13 :  9780792326045
Editeur : Springer, 1993
Couverture rigide

  • 9780792326069: Empirico-Statistical Methods of the Analysis of the Narrative Numerical Material and the Applications of the Problem of Dating

    Springer, 1994
    Couverture souple

  • 9789401714112: Empirico-Statistical Analysis of Narrative Material and its Applications to Historical Dating: Volume I: The Development of the Statistical Tools

    Springer, 2014
    Couverture souple

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Fomenko, A.T.
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Description du livre Soft Cover. Etat : new. This item is printed on demand. N° de réf. du vendeur 9789401714129

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Description du livre Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Today the methods of applied statistics have penetrated very different fields of knowledge, including the investigation oftexts ofvarious origins. These 'texts' may be considered as signal sequences of different kinds, long genetic codes, graphic representations (which may be coded and represented by a 'text'), as well as actual narrative texts (for example, historical chronicles, originals, documents, etc. ). One ofthe most important problems arising here is to recognize dependent text, i. e. , texts which have a measure of 'resemblance', arising from some kind of 'common origin'. For instance, in pattern-recognition problems, it is essential to identify from a large set of 'patterns' a pattern that is 'closest' to a given one; in studying long signal sequences, it is important to recognize 'homogeneous subsequences' and the places of their junction. This includes, in particular, the well-known change-point prob lern, which is given considerable attention in mathematical statistics and the theory of stochastic processes. As applied to the study of narrative texts, the problern of recognizing depen dent and independent texts ( e . g. , chronicles) Ieads to the problern offinding texts having a common source, i. e. , the sameoriginal (such texts are naturally called dependent), or, on the contrary, having different sources (such texts are natu rally called independent). Clearly, such problems are exceedingly complicated, and therefore the appearance of new empirico-statistical recognition methods which, along with the classical approaches, may prove useful in concrete studies (e. g. , source determination) is welcome. 240 pp. Englisch. N° de réf. du vendeur 9789401714129

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Description du livre Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Today the methods of applied statistics have penetrated very different fields of knowledge, including the investigation oftexts ofvarious origins. These texts may be considered as signal sequences of different kinds, long genetic codes, graphic representa. N° de réf. du vendeur 5837022

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Description du livre Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Today the methods of applied statistics have penetrated very different fields of knowledge, including the investigation oftexts ofvarious origins. These 'texts' may be considered as signal sequences of different kinds, long genetic codes, graphic representations (which may be coded and represented by a 'text'), as well as actual narrative texts (for example, historical chronicles, originals, documents, etc. ). One ofthe most important problems arising here is to recognize dependent text, i. e. , texts which have a measure of 'resemblance', arising from some kind of 'common origin'. For instance, in pattern-recognition problems, it is essential to identify from a large set of 'patterns' a pattern that is 'closest' to a given one; in studying long signal sequences, it is important to recognize 'homogeneous subsequences' and the places of their junction. This includes, in particular, the well-known change-point prob lern, which is given considerable attention in mathematical statistics and the theory of stochastic processes. As applied to the study of narrative texts, the problern of recognizing depen dent and independent texts ( e . g. , chronicles) Ieads to the problern offinding texts having a common source, i. e. , the sameoriginal (such texts are naturally called dependent), or, on the contrary, having different sources (such texts are natu rally called independent). Clearly, such problems are exceedingly complicated, and therefore the appearance of new empirico-statistical recognition methods which, along with the classical approaches, may prove useful in concrete studies (e. g. , source determination) is welcome. N° de réf. du vendeur 9789401714129

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