Hinderer k (37 Ergebnisse)

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Broschiert. Zustand: Gut. VI, 160 Seiten : graph. Darst.; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); leichte altersbedingte Anbräunung des Papiers; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 320.…

Paperback/ broschiert. Zustand: Gut. 160 S. Guter Zustand/ Good Ex-Library. Brownish paper. Stamped edges. Cover edges faded. Sprache: Englisch Gewicht in Gramm: 315.

Softcover. Corner of covers and pages lightly bumped; inked number on front cover; embossed ownership stamp on title page; otherwise very good condition. Inscribed by author on title page. . 247p.

Paperback. German language. Berlin: Springer-Verlag, 1972. Wraps. 247pp. Title page clipped, else VG condition.

Broschiert. Zustand: Gut. ca. 200 Seiten in getr. Zählung. Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.). Einband lichtrandig, ansonsten ordentlicher Erhaltungszustand. Sprache: Deutsch Gewicht in Gramm: 220. …

8° , Broschiert. Zustand: Gut. 247 Seiten, Einband mit kleineren Gebrauchsspuren, Namenszug auf dem Titel, Zustand gut, gering unfrisch Sprache: Deutsch Gewicht in Gramm: 510.

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Gr.-8°, Softcover/Paperback. 1.Auflage.. 160 Seiten Einband etwas berieben, Bibl.Ex., sonst guter und sauberer Zustand Sprache: Englisch Gewicht in Gramm: 360.

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Zustand: New. pp. 172.

Paperback. Zustand: Brand New. 172 pages. 10.00x7.01x0.39 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results.…

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Zustand: New. pp. 258.

4to. 8, 247, (1) S. m. mehreren Fig. OKart. Mit handschriftlicher Widmung des Verfassers. Sprache: Deutsch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - I. Diskrete Wahrscheinlichkeitsräume.- 1 Zufällige Experimente und der empirische Wahrscheinlichkeitsbegriff.- 2 Mengenoperationen und Mengenidentitäten.- 3 Der mathematische Wahrscheinlichkeitsbegriff.- 4 Diskrete Gleichverteilung und Grundformeln der Kombinatorik.- 5 Diskrete Zufallsvariable und Verteilungen.- 6 Elementare bedingte Wahrscheinlichkeiten.- 7 Bedingte Zähldichten und W-Maße in Produktmerkmalräumen.- 8 Stochastische Unabhängigkeit.- 9 Erwartungswert und Varianz.- 10 Erzeugende Funktionen.- 11 Die wichtigsten diskreten Verteilungen.- II. Hilfsmittel aus der Maß- und Integrationstheorie.- 12 Die Konstruktion von nicht-diskreten wahrscheinlichkeitstheoretischen Modellen als Fortsetzungsproblem der Maßtheorie.- 13 -Algebren.- 14 Weitere Mengensysteme.- 15 Maße.- 16 Eindeutigkeits- und Fortsetzungssatz für Maße.- 17 Meßbare Funktionen.- 18 Der Integralbegriff.- 19 Eigenschaften des Integrals.- 20 Maße in Produktmeßräumen.- III. Allgemeine Wahrscheinlichkeitsräume.- 21 Klassifikation von W-Maßen und der allgemeine Dichtebegriff.- 22 W-Maße mit Lebesgue-Dichten.- 23 Bedingte Verteilungen und W-Maße in Produktmerkmalräumen.- 24 Stochastische Unabhängigkeit im allgemeinen Fall.- 25 Erwartungswert, Varianz und Kovarianzmatrix.- 26 Bedingte Erwartungswerte.- 27 Laplace-Transformierte und charakteristische Funktionen.- 28 Die wichtigsten Verteilungen mit Lebesgue-Dichten.- 29 Ausblick auf Probleme bei unendlichen Familien von Zufallsvariablen.- Anhang 1: Bezeichnungen und Vereinbarungen über Mengen und Abbildungen.- 2: Die erweitert reellen Zahlen.- 3: Zur Kommutativität und Assoziativität von unendlichen Reihen.- Verzeichnis der verwendeten Abkürzungen und Symbole.…

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Paperback. Zustand: Brand New. 1. aufl. 1972. 3. korr. nachdruck edition. 256 pages. German language. 9.45x6.46x0.79 inches. In Stock.

paperback. Zustand: Gut. 247 Seiten; *** ACHTUNG! Das Buch kann Kellergeruch haben. M26-08-B-07-G Sprache: Deutsch Gewicht in Gramm: 1.

Zustand: gut. 1972. Grundbegriffe der Wahrscheinlichkeitstheorie In deutscher Sprache. pages.

PF. Zustand: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results. 172 pp. Englisch.…

Zustand: New. Print on Demand pp. 172 66:B&W 7 x 10 in or 254 x 178 mm Perfect Bound on White w/Gloss Lam.

Zustand: New. PRINT ON DEMAND pp. 172.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes th.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 172 pp. Englisch.…