TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Spachmann, Christoph A1 - Englert, Stefan T1 - A First Course on Time Series Analysis : Examples with SAS [Version 2012.August.01] N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - Box-Jenkins-Verfahren KW - SAS KW - Zustandsraummodelle KW - Time Series Analysis KW - State-Space Models KW - Frequency Domain KW - Box–Jenkins Program Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-72617 N1 - Version: 2012-August-01 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Tewes, Bernward A1 - Dinges, Peter A1 - Spachmann, Christoph A1 - Englert, Stefan T1 - A First Course on Time Series Analysis : Examples with SAS N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - Box-Jenkins-Verfahren KW - SAS KW - Zustandsraummodelle KW - Time Series Analysis KW - State-Space Models KW - Frequency Domain KW - Box–Jenkins Program Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-56489 N1 - Version: 2011-March-01 ER - TY - THES A1 - Hofmann, Daniel T1 - Characterization of the D-Norm Corresponding to a Multivariate Extreme Value Distribution T1 - Eine Charakterisierung der D-Norm einer multivariaten Extremwertverteilung N2 - It is well-known that a multivariate extreme value distribution can be represented via the D-Norm. However not every norm yields a D-Norm. In this thesis a necessary and sufficient condition is given for a norm to define an extreme value distribution. Applications of this theorem includes a new proof for the bivariate case, the Pickands dependence function and the nested logistic model. Furthermore the GPD-Flow is introduced and first insights were given such that if it converges it converges against the copula of complete dependence. N2 - Es ist wohlbekannt dass sich eine multivariate Extremwertverteilung mittels der D-Norm darstellen lässt. Jedoch liefert nicht jede Norm eine D-Norm. In dieser Arbeit wird eine notwendige und hinreichende Bedingung an eine Norm hergeleitet, so dass diese Norm eine Extremwertverteilung definiert. Anwendungen dieses Satzes sind unter anderem einer neuer Beweis für den bivariaten Fall, die Pickands Abhängigkeitsfunktion und das Nestes Logistic Model. Desweiteren wird der GPD-Fluss eingeführt und erste Untersuchungen wurden durchgeführt. Zum Beispiel die Tatsache, dass wenn der GPD-Fluss konvergiert, dann gegen die Copula der kompletten Abhängigkeit. KW - Kopula KW - Extremwertverteilung KW - D-Norm KW - multivariate Extreme Value Distribution KW - GPD KW - GPD-Flow KW - Copula Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-41347 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Tewes, Bernward A1 - Dinges, Peter T1 - A First Course on Time Series Analysis : Examples with SAS N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS Statistical Analysis System). Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first two chapters can be dealt with in the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 3, 4 and 5 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific part, including the diagrams generated with SAS, always starts with a computer symbol, representing the beginning of a session at the computer, and ends with a printer symbol for the end of this session. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - SAS KW - Zeitreihenanalyse KW - SAS KW - Time series analyses KW - SAS Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-12593 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Tewes, Bernward A1 - Dinges, Peter T1 - A First Course on Time Series Analysis : Examples with SAS N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS Statistical Analysis System). Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first two chapters can be dealt with in the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 3, 4 and 5 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific part, including the diagrams generated with SAS, always starts with a computer symbol, representing the beginning of a session at the computer, and ends with a printer symbol for the end of this session. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - SAS KW - Zeitreihenanalyse KW - SAS KW - Time series analyses KW - SAS Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-16919 ER - TY - JOUR A1 - Liedtke, Daniel A1 - Hofmann, Christine A1 - Jakob, Franz A1 - Klopocki, Eva A1 - Graser, Stephanie T1 - Tissue-Nonspecific Alkaline Phosphatase—A Gatekeeper of Physiological Conditions in Health and a Modulator of Biological Environments in Disease JF - Biomolecules N2 - Tissue-nonspecific alkaline phosphatase (TNAP) is a ubiquitously expressed enzyme that is best known for its role during mineralization processes in bones and skeleton. The enzyme metabolizes phosphate compounds like inorganic pyrophosphate and pyridoxal-5′-phosphate to provide, among others, inorganic phosphate for the mineralization and transportable vitamin B6 molecules. Patients with inherited loss of function mutations in the ALPL gene and consequently altered TNAP activity are suffering from the rare metabolic disease hypophosphatasia (HPP). This systemic disease is mainly characterized by impaired bone and dental mineralization but may also be accompanied by neurological symptoms, like anxiety disorders, seizures, and depression. HPP characteristically affects all ages and shows a wide range of clinical symptoms and disease severity, which results in the classification into different clinical subtypes. This review describes the molecular function of TNAP during the mineralization of bones and teeth, further discusses the current knowledge on the enzyme’s role in the nervous system and in sensory perception. An additional focus is set on the molecular role of TNAP in health and on functional observations reported in common laboratory vertebrate disease models, like rodents and zebrafish. KW - TNAP KW - hypophosphatasia KW - HPP KW - zebrafish KW - mineralization KW - ALPL KW - craniosynostosis KW - teeth KW - nervous system Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-220096 SN - 2218-273X VL - 10 IS - 12 PB - MDPI ER -