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
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
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
3907
1993
eng
article
1
2010-04-26
--
--
Von Mises condition revisited
It is shown that the rate of convergence in the von Mises conditions of extreme value theory determines the distance of the underlying distribution function F from a generalized Pareto distribution. The distance is measured in terms of the pertaining densities with the limit being ultimately attained if and only if F is ultimately a generalized Pareto distribution. Consequently, the rate of convergence of the extremes in an lid sample, whether in terms of the distribution of the largest order statistics or of corresponding empirical truncated point processes, is determined by the rate of convergence in the von Mises condition. We prove that the converse is also true.
urn:nbn:de:bvb:20-opus-45790
4579
In: The Annals of Probability (1993) 21, 3, 1310 - 1328
Michael Falk
Frank Marohn
eng
uncontrolled
Von Mises conditions
eng
uncontrolled
extreme value theory
eng
uncontrolled
extreme value distribution
eng
uncontrolled
extreme order statistics
eng
uncontrolled
generalized Pareto distribution
Mathematik
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3907/Marohn_Mises_condition.pdf
3908
1994
eng
article
1
2010-04-26
--
--
On statistical information of extreme order statistics, local extreme value alternatives, and Poisson point processes
The aim of the present paper is to clarify the role of extreme order statistics in general statistical models. This is done within the general setup of statistical experiments in LeCam's sense. Under the assumption of monotone likelihood ratios, we prove that a sequence of experiments is asymptotically Gaussian if, and only if, a fixed number of extremes asymptotically does not contain any information. In other words: A fixed number of extremes asymptotically contains information iff the Poisson part of the limit experiment is non-trivial. Suggested by this result, we propose a new extreme value model given by local alternatives. The local structure is described by introducing the space of extreme value tangents. It turns out that under local alternatives a new class of extreme value distributions appears as limit distributions. Moreover, explicit representations of the Poisson limit experiments via Poisson point processes are found. As a concrete example nonparametric tests for Frechet type distributions against stochastically larger alternatives are treated. We find asymptotically optimal tests within certain threshold models.
urn:nbn:de:bvb:20-opus-45816
4581
In: Journal of Multivariate Analysis (1994) 48, 1, 1- 30
A. Janssen
Frank Marohn
Mathematik
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3908/Marohn_Statistical_information.pdf
3909
1994
eng
conferenceobject
1
2010-04-26
--
--
On testing the exponential and Gumbel distribution
No abstract available
urn:nbn:de:bvb:20-opus-45804
4580
In: Extreme Value Theory and Applications / J. Galambos et al. (eds.). - Dordrecht: Kluwer Academic Press, 1994, 1, 159 - 174
Frank Marohn
deu
swd
Gumbel-Verteilung
deu
swd
Extremal–I–Verteilung
eng
uncontrolled
generalized Pareto distribution
eng
uncontrolled
extreme value distribution
Mathematik
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3909/Marohn_Gumbel_distribution.pdf
3910
1990
eng
book
1
2010-04-27
--
--
On statistical information of extreme order statistics
No abstract available
urn:nbn:de:bvb:20-opus-47866
4786
Zugl.: Siegen, Univ.-Gesamthochschule, Diss., 1990
On statistical information of extreme order statistics / Frank Marohn. - Siegen: Univ.-Gesamthochschule, 1990
Frank Marohn
deu
swd
Rangstatistik
deu
swd
Extremwert
deu
swd
Statistik
Mathematik
Extreme value theory; extremal processes
Order statistics; empirical distribution functions
Statistics of extreme values; tail inference
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3910/Marohn_Extreme_order_statistics.pdf
3911
1993
eng
article
1
2010-04-27
--
--
Asymptotically optimal tests for conditional distributions
No abstract available
urn:nbn:de:bvb:20-opus-45823
4582
In: The Annals of Statistics (1993) 21, 1, 45 - 60
Michael Falk
Frank Marohn
Mathematik
Point processes
Asymptotic distribution theory
Order statistics; empirical distribution functions
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3911/Marohn_Asymptotic_tests.pdf
3912
1994
eng
article
1
2010-04-27
--
--
Asymptotic sufficiency of order statistics for almost regular Weibull type densities
Consider a location family which is defined via a Weibull type density having shape parameter a = 1. We treat the problem, which portion of the order statistics is asymptotically sufficient. It turns out that the intermediate order statistics are relevant.
urn:nbn:de:bvb:20-opus-45837
4583
In: Statistics & Decisions, 1994, 12, 385 - 393
Frank Marohn
eng
uncontrolled
Weibull type density
eng
uncontrolled
intermediate order statistics
eng
uncontrolled
asymptotic sufficiency
eng
uncontrolled
local asymptotic normality
Mathematik
Order statistics; empirical distribution functions
open_access
Institut für Mathematik
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/3912/Marohn_Asymptotic_sufficiency.pdf