multivariate statistical modelling based von fahrmeir ludwig (16 Ergebnisse)

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780387942339.

Zustand: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Re-bound by library. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:0387942335.

Hardcover. Octavo; G+; Hardcover; Spine, yellow with white print; Boards in yellow cloth with white and brown print, toning to spine, vendor label on rear, else clean and strong; Text block clean and tight; xxiv, 425 pages, "With 45 illustrations". 1364243. FP New Rockville Stock.

gebundene Ausgabe. Zustand: Gut. XXIV, 425 S. : graph. Darst. Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 830.

gebundene Ausgabe. Zustand: Gut. XXIV, 425 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); Schnitt und Einband sind etwas staubschmutzig; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut.In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 800.

gebundene Ausgabe. Zustand: Gut. XXIV, 425 Seiten; Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. Sprache: Englisch Gewicht in Gramm: 780.

Hardcover. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less 2.07.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 548 | Sprache: Englisch | Produktart: Bücher.

Zustand: Gut. Zustand: Gut | Seiten: 548 | Sprache: Englisch | Produktart: Bücher.

Zustand: New. In.

Zustand: New. In.

Buch. Zustand: Neu. Neuware -Since our first edition of this book, many developments in statistical mod elling based on generalized linear models have been published, and our primary aim is to bring the book up to date. Naturally, the choice of these recent developments reflects our own teaching and research interests. The new organization parallels that of the first edition. We try to motiv ate and illustrate concepts with examples using real data, and most data sets are available on http:/ f stat. uni-muenchen. de/welcome_e. html, with a link to data archive. We could not treat all recent developments in the main text, and in such cases we point to references at the end of each chapter. Many changes will be found in several sections, especially with those connected to Bayesian concepts. For example, the treatment of marginal models in Chapter 3 is now current and state-of-the-art. The coverage of nonparametric and semiparametric generalized regression in Chapter 5 is completely rewritten with a shift of emphasis to linear bases, as well as new sections on local smoothing approaches and Bayesian inference. Chapter 6 now incorporates developments in parametric modelling of both time series and longitudinal data. Additionally, random effect models in Chapter 7 now cover nonparametric maximum likelihood and a new section on fully Bayesian approaches. The modifications and extensions in Chapter 8 reflect the rapid development in state space and hidden Markov models.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 548 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -Since our first edition of this book, many developments in statistical mod elling based on generalized linear models have been published, and our primary aim is to bring the book up to date. Naturally, the choice of these recent developments reflects our own teaching and research interests. The new organization parallels that of the first edition. We try to motiv ate and illustrate concepts with examples using real data, and most data sets are available on http:/ f stat. uni-muenchen. de/welcome_e. html, with a link to data archive. We could not treat all recent developments in the main text, and in such cases we point to references at the end of each chapter. Many changes will be found in several sections, especially with those connected to Bayesian concepts. For example, the treatment of marginal models in Chapter 3 is now current and state-of-the-art. The coverage of nonparametric and semiparametric generalized regression in Chapter 5 is completely rewritten with a shift of emphasis to linear bases, as well as new sections on local smoothing approaches and Bayesian inference. Chapter 6 now incorporates developments in parametric modelling of both time series and longitudinal data. Additionally, random effect models in Chapter 7 now cover nonparametric maximum likelihood and a new section on fully Bayesian approaches. The modifications and extensions in Chapter 8 reflect the rapid development in state space and hidden Markov models.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 548 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Since our first edition of this book, many developments in statistical mod elling based on generalized linear models have been published, and our primary aim is to bring the book up to date. Naturally, the choice of these recent developments reflects our own teaching and research interests. The new organization parallels that of the first edition. We try to motiv ate and illustrate concepts with examples using real data, and most data sets are available on http:/ f stat. uni-muenchen. de/welcome_e. html, with a link to data archive. We could not treat all recent developments in the main text, and in such cases we point to references at the end of each chapter. Many changes will be found in several sections, especially with those connected to Bayesian concepts. For example, the treatment of marginal models in Chapter 3 is now current and state-of-the-art. The coverage of nonparametric and semiparametric generalized regression in Chapter 5 is completely rewritten with a shift of emphasis to linear bases, as well as new sections on local smoothing approaches and Bayesian inference. Chapter 6 now incorporates developments in parametric modelling of both time series and longitudinal data. Additionally, random effect models in Chapter 7 now cover nonparametric maximum likelihood and a new section on fully Bayesian approaches. The modifications and extensions in Chapter 8 reflect the rapid development in state space and hidden Markov models.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Since our first edition of this book, many developments in statistical mod elling based on generalized linear models have been published, and our primary aim is to bring the book up to date. Naturally, the choice of these recent developments reflects our own teaching and research interests. The new organization parallels that of the first edition. We try to motiv ate and illustrate concepts with examples using real data, and most data sets are available on http:/ f stat. uni-muenchen. de/welcome_e. html, with a link to data archive. We could not treat all recent developments in the main text, and in such cases we point to references at the end of each chapter. Many changes will be found in several sections, especially with those connected to Bayesian concepts. For example, the treatment of marginal models in Chapter 3 is now current and state-of-the-art. The coverage of nonparametric and semiparametric generalized regression in Chapter 5 is completely rewritten with a shift of emphasis to linear bases, as well as new sections on local smoothing approaches and Bayesian inference. Chapter 6 now incorporates developments in parametric modelling of both time series and longitudinal data. Additionally, random effect models in Chapter 7 now cover nonparametric maximum likelihood and a new section on fully Bayesian approaches. The modifications and extensions in Chapter 8 reflect the rapid development in state space and hidden Markov models.