Librería: SecondSale, Montgomery, IL, Estados Unidos de America
EUR 86,03
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: Acceptable. Item in acceptable condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
EUR 94,42
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 97,57
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritohardcover. Condición: Very Good. Cover and edges may have some wear.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 105,74
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: New.
EUR 109,42
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: New.
Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 121,02
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritohardcover. Condición: Good. Cover and edges may have some wear. Loose binding, good reading copy.
EUR 108,10
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: Like New. Like New. book.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 131,20
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Publicado por Springer Berlin Heidelberg, 2023
ISBN 10: 3662638843 ISBN 13: 9783662638842
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 117,69
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book's dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented.The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference.In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book.The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
EUR 148,63
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritopaperback. Condición: New. 2nd ed. 2021. Special order direct from the distributor.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 156,06
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 143,83
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 143,82
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 161,68
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 163,73
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 165,90
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 164,67
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Alemania
EUR 141,99
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: gut. 2013. The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference. Autor: Ludwig Fahrmeir is Professor emeritus at the Department of Statistics at Ludwig-Maximilians-University Munich. From 1995 to 2006 he was speaker of the Collaborative Research Center 'Statistical Analysis of Discrete Data', supported financially by the German National Science Foundation. His main research interests are semiparametric regression, longitudinal data analysis and spatial statistics, with applications ranging from social science and risk management to public health and neuroscience. - Thomas Kneib is Professor for Statistics at Georg August University Göttingen, Germany, where he is speaker of the interdisciplinary Centre for Statistics and a Research Training Group on "Scaling Problems in Statistics". He received his PhD in Statistics at Ludwig-Maximilians-University Munich and, during his PostDoc phase, has been Visiting Professor for Applied Statistics at the University of Ulm and Substitute Professor for Statistics at Georg-August-University Göttingen. From 2009 until 2011 he has been Professor for Applied Statistics at Carl von Ossietzky University Oldenburg. His main research interests include semiparametric regression, spatial statistics and quantile regression. - Stefan Lang is Professor for Applied Statistics at University of Innsbruck, Austria. He received his PhD at Ludwig-Maximilians-University Munich. From 2005 to 2006 he has been Professor for Statistics at University of Leipzig. He is currently editor of Advances of Statistical Analysis and Associate Editor of Statistical Modelling. His main research interests include semiparametric and spatial regression, multilevel modelling and complex Bayesian models, with applications among others in environmetrics, marketing science, real estate and actuarial science. - Brian D. Marx is a full professor in the Department of Experimental Statisitics at Louisiana State University. His main research interests include P-spline smoothiing, ill-conditioned regression problems, and high-dimensional chemometric applications. He is currently serving as coordinating editor for the journal Statistical Modelling and is past chair of the Statistical Modelling Society. Content: Introduction.- Regression Models.- The Classical Linear Model.- Extensions of the Classical Linear Model.- Generalized Linear Models.- Categorical Regression Models.- Mixed Models.- Nonparametric Regression.- Structured Additive Regression.- Quantile Regression.- A Matrix Algebra.- B Probability Calculus and Statistical Inference.- Bibliography.- Index. Zusatzinfo XIV, 698 p. Verlagsort Berlin Sprache englisch Maße 155 x 235 mm Mathematik / Informatik Mathematik Wirtschaft Lexika Generalized Linear Models linear regression mixed models Regression Statistik Semiparametric Regression spatial regression Wirtschaftsstatistik ISBN-10 3-642-34332-5 / 3642343325 ISBN-13 978-3-642-34332-2 / 9783642343322 In englischer Sprache. 650 pages. 15,6 x 3,8 x 23,4 cm.
EUR 164,37
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: Brand New. 2013 edition. 698 pages. 9.25x6.10x1.61 inches. In Stock.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 163,05
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 183,50
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 169,10
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 185,33
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 167,05
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Alemania
EUR 151,99
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: gut. Rechnung mit MwSt - Versand aus Deutschland pages.
EUR 177,39
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 2nd edition. 766 pages. 9.25x6.10x1.53 inches. In Stock.
Publicado por Springer Berlin Heidelberg Mär 2022, 2022
ISBN 10: 3662638819 ISBN 13: 9783662638811
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book's dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented.The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference.In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book.The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
Publicado por Springer, Berlin, Springer Berlin Heidelberg, Springer, 2013
ISBN 10: 3642343325 ISBN 13: 9783642343322
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 166,41
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.
EUR 218,63
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: Like New. Like New. book.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 228,33
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.