Stefan Lang - Böcker

This volume provides a comprehensive account of Friedrich Schleiermacher’s philosophy of religion. The contributors cover the historical context of Schleiermacher’s work, specific aspects of his philosophy of religion, and the ways that his work can contribute to contemporary debates.Friedrich Schleiermacher is considered one of the outstanding representatives of 19th‑century Protestant theology. This volume brings together scholars from both continental and analytic traditions to explore Schleiermacher’s preeminent role in post‑Kantian philosophy of religion. The chapters are divided into three thematic sections. The first section situates Schleiermacher in the context of the 18th- and 19th‑century philosophy of religion. These chapters analyze his relation to thinkers such as Kant, Fichte, Hegel, Schelling, and also to Kierkegaard and Heidegger, as well as to prominent theologians in the Protestant and Catholic traditions. The second section explores different aspects of Schleiermacher’s philosophy of religion such as absolute dependence or religious feeling. Finally, the third section addresses how Schleiermacher’s insights can contribute to contemporary philosophy of religion. These chapters address current debates, particularly on religious experience, feminism, and philosophy of emotions.Friedrich Schleiermacher’s Philosophy of Religion will be of interest to scholars and advanced students working in philosophy of religion, history of philosophy, and 19th‑century religious thought.

The self, self-awareness and emotions are central subjects within contemporary philosophy of mind but comparatively little attention has been paid to the relationships between them. This volume brings together philosophers from different specialisms to explore these relationships from three different angles.

The self, self-awareness and emotions are central subjects within contemporary philosophy of mind but comparatively little attention has been paid to the relationships between them.This volume brings together philosophers from different specialisms to explore these relationships from three different angles. First, whether a theory of self-awareness can contribute to a theory of emotion, including how different aspects and kinds of self-awareness are related to different emotions. Second, from the opposite direction, whether research into emotions can help achieve a better understanding of self-consciousness. Finally, the book considers how emotions are involved in the nature and development of selves.Self and Affect is essential reading for all scholars and researchers of the philosophy of mind, especially those focussing on emotions and self-awareness.

Die klassische deutsche Philosophie zählt zu den bedeutendsten und wirkmächtigsten Diskursformationen. Die Beiträge bieten eine grundlegende Orientierung sowie systematische Analysen zu Schlüsselbegriffen und Grundproblemen der praktischen Philosophie dieser Epoche. Neben den Klassikern wie Kant, Fichte und Hegel werden auch Beziehungen zu aktuellen Debatten behandelt und analysiert.

Datenbanken spielen als Informationsspeicher immer mehr eine zentrale Rolle. Daher müssen ihr erfolgreicher Aufbau und ihr fehlerfreier Betrieb langfristig gesichert sein. Umfassende Kenntnisse der verwendeten Modelle, der verschiedenen Entwurfstechniken sowie der beim laufenden Betrieb zu beachtenden Maßregeln sind dazu notwendig. Das Buch widmet sich diesen Themen vor allem unter dem Aspekt der Datenbanknutzung. So kann der Praktiker die behandelten Konzepte und Techniken sofort anwenden. Ebenso bietet es Studierenden und Wissenschaftlern fundierte Information über aktuelle Techniken und Trends (verteilte datenintensive Anwendungen, Migration auf moderne Plattformen, Standardisierung).Drei durchgängige Anwendungsbeispiele ermöglichen den Vergleich unterschiedlicher Lösungsmethoden.

This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).

Dieses Arbeitsbuch ergänzt perfekt das Lehrbuch Fahrmeir/Künstler/Pigeot/Tutz: Statistik - Der Weg zur Datenanalyse. Es dient damit der Vertiefung und der Einübung des im Lehrbuch vermittelten Stoffes zur Wahrscheinlichkeitsrechnung, deskriptiven und induktiven Statistik.

In dieser Einführung werden erstmals klassische Regressionsansätze und moderne nicht- und semiparametrische Methoden in einer integrierten, einheitlichen und anwendungsorientierten Form beschrieben. Die Darstellung wendet sich an Studierende der Statistik in Wahl- und Hauptfach sowie an empirisch-statistisch und interdisziplinär arbeitende Wissenschaftler und Praktiker, zum Beispiel in Wirtschafts- und Sozialwissenschaften, Bioinformatik, Biostatistik, Ökonometrie, Epidemiologie. Die praktische Anwendung der vorgestellten Konzepte und Methoden wird anhand ausführlich vorgestellter Fallstudien demonstriert, um dem Leser die Analyse eigener Fragestellungen zu ermöglichen.

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.

Datenbanken spielen als Informationsspeicher immer mehr eine zentrale Rolle. Daher müssen ihr erfolgreicher Aufbau und ihr fehlerfreier Betrieb langfristig gesichert sein. Umfassende Kenntnisse der verwendeten Modelle, der verschiedenen Entwurfstechniken sowie der beim laufenden Betrieb zu beachtenden Maßregeln sind dazu notwendig. Das Buch widmet sich diesen Themen vor allem unter dem Aspekt der Datenbanknutzung. So kann der Praktiker die behandelten Konzepte und Techniken sofort anwenden. Ebenso bietet es Studierenden und Wissenschaftlern fundierte Information über aktuelle Techniken und Trends (verteilte datenintensive Anwendungen, Migration auf moderne Plattformen, Standardisierung).Drei durchgängige Anwendungsbeispiele ermöglichen den Vergleich unterschiedlicher Lösungsmethoden.

This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).

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.

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.

Performativität spielt avant la lettre in der Klassischen Deutschen Philosophie eine bedeutende Rolle. Sie ist u.a. ein zentraler Bestandteil originärer Interpretationen des Absoluten, des Subjekts oder auch des Wissens. Seit den 2010er Jahren mehren sich daher Untersuchungen, die dem Performativen bei Kant, Fichte, Schelling, Hegel und in der Frühromantik nachspüren. Dieser Sammelband greift diese Entwicklung auf. Anhand interdisziplinärer Beiträge wird Performativität innerhalb der Klassischen Deutschen Philosophie erläutert und diskutiert. Dabei wird der hermeneutische und systematische Ertrag performativer Interpretationen dargestellt.

Dieses Arbeitsbuch bietet 227 Aufgaben mit vollständigen Lösungen – ideal zum Üben, Wiederholen und zur Klausurvorbereitung. Viele der Aufgaben sind als Übungen mit dem Statistikprogramm R konzipiert und nutzen digital bereitgestellte Datensätze.Abgedeckte Themen sind insbesondere: Grundlagen der Stochastik, deskriptive und explorative Datenanalyse, induktive Statistik, Regressions- und Varianzanalyse sowie Zeitreihenanalyse.Das Arbeitsbuch ist dabei inhaltlich und strukturell auf das Lehrbuch Statistik – Der Weg zur Datenanalyse von Fahrmeir/Heumann/Künstler/Pigeot/Tutz in der 9. Auflage abgestimmt: Alle 99 Aufgaben aus dem Lehrbuch werden hier ausführlich gelöst und durch Verweise eng mit diesem verknüpft. Beide Bücher sind aber auch unabhängig voneinander nutzbar.Für die vorliegende 6. Auflage des Arbeitsbuchs wurden etliche Aufgaben neu aufgenommen bzw. bisherige Aufgaben durch aktuellere ersetzt.