6130
2012
eng
book
Universität Heidelberg / Institut für medizinische Biometrie und Informatik
1
2012-09-03
--
--
A First Course on Time Series Analysis : Examples with SAS [Version 2012.August.01]
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.
urn:nbn:de:bvb:20-opus-72617
7261
Version: 2012-August-01
http://statistik.mathematik.uni-wuerzburg.de/timeseries/
Michael Falk
Frank Marohn
René Michel
Daniel Hofmann
Maria Macke
Christoph Spachmann
Stefan Englert
deu
swd
Zeitreihenanalyse
deu
swd
Box-Jenkins-Verfahren
deu
swd
SAS <Programm>
deu
uncontrolled
Zustandsraummodelle
eng
uncontrolled
Time Series Analysis
eng
uncontrolled
State-Space Models
eng
uncontrolled
Frequency Domain
eng
uncontrolled
Box–Jenkins Program
Mathematik
Time series analysis
Time series, auto-correlation, regression, etc. [See also 91B84]
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/6130/2012_August_01_times_rawdata.zip
https://opus.bibliothek.uni-wuerzburg.de/files/6130/2012_August_01_times_series_analysis.pdf
https://opus.bibliothek.uni-wuerzburg.de/files/6130/2012_August_01_times_source.zip
4800
2011
eng
book
Universität Würzburg / Lehrstuhl für Statistik
Universität Heidelberg / Institut für medizinische Biometrie und Informatik
1
2011-05-11
--
--
A First Course on Time Series Analysis : Examples with SAS
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.
urn:nbn:de:bvb:20-opus-56489
5648
Version: 2011-March-01
http://statistik.mathematik.uni-wuerzburg.de/timeseries/
Deutsches Urheberrecht
Michael Falk
Frank Marohn
René Michel
Daniel Hofmann
Maria Macke
Bernward Tewes
Peter Dinges
Christoph Spachmann
Stefan Englert
deu
swd
Zeitreihenanalyse
deu
swd
Box-Jenkins-Verfahren
deu
swd
SAS <Programm>
deu
uncontrolled
Zustandsraummodelle
eng
uncontrolled
Time Series Analysis
eng
uncontrolled
State-Space Models
eng
uncontrolled
Frequency Domain
eng
uncontrolled
Box–Jenkins Program
Mathematik
Time series analysis
Time series, auto-correlation, regression, etc. [See also 91B84]
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/4800/2011_March_01_times.pdf
3454
2009
eng
doctoralthesis
1
2009-12-15
--
2009-12-03
Characterization of the D-Norm Corresponding to a Multivariate Extreme Value Distribution
Eine Charakterisierung der D-Norm einer multivariaten Extremwertverteilung
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.
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.
urn:nbn:de:bvb:20-opus-41347
4134
X122729
Daniel Hofmann
deu
swd
Kopula <Mathematik>
deu
swd
Extremwertverteilung
eng
uncontrolled
D-Norm
eng
uncontrolled
multivariate Extreme Value Distribution
eng
uncontrolled
GPD
eng
uncontrolled
GPD-Flow
eng
uncontrolled
Copula
Mathematik
open_access
Institut für Mathematik
Universität Würzburg
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3454/Characterization_of_the_D_Norm.pdf
1444
2006
eng
book
Universität Würzburg / Lehrstuhl für Statistik
1
2006-02-16
--
--
A First Course on Time Series Analysis : Examples with SAS
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.
1691
urn:nbn:de:bvb:20-opus-16919
http://statistik.mathematik.uni-wuerzburg.de/timeseries/
Michael Falk
Frank Marohn
René Michel
Daniel Hofmann
Maria Macke
Bernward Tewes
Peter Dinges
deu
swd
Zeitreihenanalyse
deu
swd
SAS <Programm>
deu
uncontrolled
Zeitreihenanalyse
deu
uncontrolled
SAS
eng
uncontrolled
Time series analyses
eng
uncontrolled
SAS
Mathematik
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/1444/2006-February-01-programs.zip
https://opus.bibliothek.uni-wuerzburg.de/files/1444/2006-February-01-rawdata.zip
https://opus.bibliothek.uni-wuerzburg.de/files/1444/2006-February-01-times.pdf
1070
2005
eng
book
Universität Würzburg / Lehrstuhl für Statistik , Universität Eichstätt/Rechenzentrum
1
2005-04-07
--
--
A First Course on Time Series Analysis : Examples with SAS
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.
urn:nbn:de:bvb:20-opus-12593
1259
http://statistik.mathematik.uni-wuerzburg.de/timeseries/
Michael Falk
Frank Marohn
René Michel
Daniel Hofmann
Maria Macke
Bernward Tewes
Peter Dinges
deu
swd
Zeitreihenanalyse
deu
swd
SAS <Programm>
deu
uncontrolled
Zeitreihenanalyse
deu
uncontrolled
SAS
eng
uncontrolled
Time series analyses
eng
uncontrolled
SAS
Mathematik
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/1070/times_rawdata.zip
https://opus.bibliothek.uni-wuerzburg.de/files/1070/times_sasdata.zip
https://opus.bibliothek.uni-wuerzburg.de/files/1070/timesseries.pdf