empirico statistical analysis narrative material di fomenko a t (32 risultati)

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - We present certain empirico-statistical methods for the analysis of narrative and nu merical data extracted from different texts of historical character such as chronicles or annals. They are based on several statistical principles worked out by the author, and originally reported at the Third International Vilnius Conference on Probability Theory and Mathematical Statistics in 1981. The principal results were published in the papers [15]-[32], [293]-[299], [304]-[319] and in the book: A. T. Fomenko, Methods for Statistical Analysis of Narrative Texts and Applications to Chronol ogy, Moscow Univ. Press, Moscow, 1990 (in Russian). See also Part 1. The methods are applied to the problem of correct dating of the events in ancient and medieval history. These results induce conjectures on the redating of some important ancient historical events. Generally speaking, we might say that the commonly accepted 'Modern Text book' of ancient and medieval European, Mediterranean, Egyptian and Middle Eastern history is a fibered (layered) chronicle obtained by gluing together four nearly identical copies of a shorter 'original' chronicle. The other three chronicles are obtained from the 'original' chronicle by redating and renaming the events de scribed in them; we rigidly move the 'original' chronicle in its entirety backwards in time by approximately 333, 1053 and 1778 years. Thus, the full 'Modern Textbook' can be reconstructed from its smaller part, namely from the 'original' chronicle for the 9-17th cc. A.D. See Appendix 1, Figs. 101-104.

Taschenbuch. Condizione: 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.

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Buch. Condizione: 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.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - We present certain empirico-statistical methods for the analysis of narrative and nu merical data extracted from different texts of historical character such as chronicles or annals. They are based on several statistical principles worked out by the author, and originally reported at the Third International Vilnius Conference on Probability Theory and Mathematical Statistics in 1981. The principal results were published in the papers [15]-[32], [293]-[299], [304]-[319] and in the book: A. T. Fomenko, Methods for Statistical Analysis of Narrative Texts and Applications to Chronol ogy, Moscow Univ. Press, Moscow, 1990 (in Russian). See also Part 1. The methods are applied to the problem of correct dating of the events in ancient and medieval history. These results induce conjectures on the redating of some important ancient historical events. Generally speaking, we might say that the commonly accepted 'Modern Text book' of ancient and medieval European, Mediterranean, Egyptian and Middle Eastern history is a fibered (layered) chronicle obtained by gluing together four nearly identical copies of a shorter 'original' chronicle. The other three chronicles are obtained from the 'original' chronicle by redating and renaming the events de scribed in them; we rigidly move the 'original' chronicle in its entirety backwards in time by approximately 333, 1053 and 1778 years. Thus, the full 'Modern Textbook' can be reconstructed from its smaller part, namely from the 'original' chronicle for the 9-17th cc. A.D. See Appendix 1, Figs. 101-104.

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Taschenbuch. Condizione: 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.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We present certain empirico-statistical methods for the analysis of narrative and nu merical data extracted from different texts of historical character such as chronicles or annals. They are based on several statistical principles worked out by the author, and originally reported at the Third International Vilnius Conference on Probability Theory and Mathematical Statistics in 1981. The principal results were published in the papers [15]-[32], [293]-[299], [304]-[319] and in the book: A. T. Fomenko, Methods for Statistical Analysis of Narrative Texts and Applications to Chronol ogy, Moscow Univ. Press, Moscow, 1990 (in Russian). See also Part 1. The methods are applied to the problem of correct dating of the events in ancient and medieval history. These results induce conjectures on the redating of some important ancient historical events. Generally speaking, we might say that the commonly accepted 'Modern Text book' of ancient and medieval European, Mediterranean, Egyptian and Middle Eastern history is a fibered (layered) chronicle obtained by gluing together four nearly identical copies of a shorter 'original' chronicle. The other three chronicles are obtained from the 'original' chronicle by redating and renaming the events de scribed in them; we rigidly move the 'original' chronicle in its entirety backwards in time by approximately 333, 1053 and 1778 years. Thus, the full 'Modern Textbook' can be reconstructed from its smaller part, namely from the 'original' chronicle for the 9-17th cc. A.D. See Appendix 1, Figs. 101-104. 480 pp. Englisch.

Buch. Condizione: 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. 238 pp. Englisch.

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