Inhaltsbereich
Methodologische Grundlagen
Übersicht
Theorien der Imprecise Probability
- Dominik Kreiss, Georg
Schollmeyer, and Thomas Augustin.
Towards improving electoral forecasting by including undecided voters and
interval-valued prior knowledge.
In Proceedings of the Twelfth International Symposium on Imprecise
Probabilities: Theories and Applications, Proceedings of Machine
Learning Research, Granada, Spain, 06–09 Jul 2021.
- Patrick Schwaferts and Thomas
Augustin.
Imprecise hypothesis-based bayesian decision making with composite hypotheses.
In Proceedings of the Twelfth International Symposium on Imprecise
Probabilities: Theories and Applications, Proceedings of Machine
Learning Research, Granada, Spain, 06–09 Jul 2021.
- Dominik Kreiss and Thomas
Augustin.
Undecided voters as set-valued information, towards forecasts under epistemic
imprecision.
In Jesse Davis and Karim Tabia, editors,
Scalable Uncertainty Management 2020, pages 242–250. Springer,
2020.
- Dominik Kreiss, Malte Nalenz,
and Thomas Augustin.
Undecided
voters as set-valued information, machine learning approaches under complex
uncertainty.
In Eyke Huellermeier and Sebastian Destercke,
editors, ECML/PKDD 2020 Tutorial and Workshop on Uncertainty in Machine
Learning. 2020.
- Luisa
Ebner, Patrick Schwaferts, and Thomas
Augustin.
Robust Bayes factor
for independent two-sample comparisons under imprecise prior information.
In Jasper De Bock, Cassio P. de Campos,
Gert de Cooman, Erik Quaeghebeur, and
Gregory Wheeler, editors, Proceedings of the Eleventh
International Symposium on Imprecise Probability: Theories and
Applications, volume 103 of Proceedings of Machine Learning
Research, pages 167–174. PMLR, 2019.
(PDF)
- Eva Endres, Paul Fink, and
Thomas Augustin.
Imprecise imputation: A
nonparametric micro approach reflecting the natural uncertainty of
statistical matching with categorical data.
Journal of Official Statistical, 35:599–624, 2019.
- Aziz Omar and Thomas
Augustin.
Estimation of
classification probabilities in small domains accounting for nonresponse
relying on imprecise probability.
International Journal of Approximate Reasoning, 115:134–143,
2019.
Substantially extended, invited special issue version of Omar & Augustin
(2018, SMPS).
- Patrick Schwaferts and Thomas
Augustin.
Imprecise
hypothesis-based Bayesian decision making with simple hypotheses.
In Jasper De Bock, Cassio P. de Campos,
Gert de Cooman, Erik Quaeghebeur, and
Gregory Wheeler, editors, Proceedings of the Eleventh
International Symposium on Imprecise Probability: Theories and
Applications, volume 103 of Proceedings of Machine Learning
Research, pages 338–345. PMLR, 2019.
(PDF)
- Thomas Augustin.
Imprecise
sampling models for modelling unobserved heterogeneity? Basic ideas of a
credal likelihood concept.
In Davide Ciucci, Gabriella Pasi, and
Barbara Vantaggi, editors, Scalable Uncertainty
Management (Proceedings of the 12th International Conference, SUM 2018, Milan
(Italy), volume 11 of Lecture Notes in Artificial
Intelligence, pages 351–358. Springer, 2018.
- Thomas Augustin and Rudolf
Seising.
Kurt Weichselberger's
contribution to imprecise probabilities.
International Journal of Approximate Reasoning, 98:132–145, 2018.
Substantially extended, invited special issue version of Augustin & Seising
(2017, ISIPTA).
- Eva Endres, Paul Fink, and
Thomas Augustin.
Imprecise imputation: A
nonparametric micro approach reflecting the natural uncertainty of
statistical matching with categorical data.
Technical Report 214, Department of Statistics, LMU Munich, 2018.
- Paul Fink.
Contributions to
reasoning on imprecise data: Imprecise classification trees, generalized
linear regression on microaggregated data and imprecise
imputation.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Paul
Fink.
imptree:
Classification Trees with Imprecise Probabilities, 2018.
R package version 0.5.1.
- Paul Fink and Eva Endres.
impimp: Imprecise
Imputation for Statistical Matching, 2018.
R package version 0.3.0.
- Christoph
Jansen.
Some contributions to
decision making in complex information settings with imprecise probabilities
and incomplete preferences: Theoretical and algorithmic results.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Christoph Jansen, Georg
Schollmeyer, and Thomas Augustin.
Concepts for decision
making under severe uncertainty with partial ordinal and partial cardinal
preferences.
International Journal of Approximate Reasoning, 98:112–131, 2018.
Substantially extended, invited special issue version of Jansen, Schollmeyer &
Augustin (2017, ISIPTA).
- Christoph Jansen, Georg
Schollmeyer, and Thomas Augustin.
A probabilistic
evaluation framework for preference aggregation reflecting group
homogeneity.
Mathematical Social Sciences, 96:49–62, 2018.
- Aziz Omar and Thomas
Augustin.
Estimation
of classification probabilities in small domains accounting for nonresponse
relying on imprecise probability.
In Sebastien Destercke, Thierry Denoeux,
Maria Angeles Gil, Przemyslaw Grzegorzewski,
and Olgierd Hryniewicz, editors, SMPS 2018: Uncertainty
Modelling in Data Science, volume 832 of Advances in Intelligent
Systems and Computing, pages 175–182. Springer, 2018.
- Julia Plass.
Statistical modelling of
categorical data under ontic and epistemic imprecision: contributions to
power set based analyses, cautious likelihood inference and (non-)testability
of coarsening mechanism.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Thomas Augustin and Rudolf
Seising.
Kurt
Weichselberger's contribution to imprecise probabilities.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 13–24. PMLR, 2017.
- Thomas Augustin, Serena
Doria, and Mássimo Marinacci.
Imprecise probability:
Theories and applications [editorial to virtual special issue on the ninth
international symposium on imprecise probability: Theories and applications
(isipta 2015)].
International Journal of Approximate Reasoning, 84:39–40,
2017.
- Eva Endres, Paul Fink, and
Thomas Augustin.
Imprecise
imputation for statistical matching.
Poster presentation, 2017.
ISIPTA '17: Tenth International Symposium on Imprecise Probability: Theories
and Applications.
- Paul
Fink and Thomas Augustin.
(Generalized) linear
regression on microaggregated data – from nuisance parameter optimization to
partial identification.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 157–168. PMLR, 2017.
- Christoph Jansen, Thomas
Augustin, and Georg Schollmeyer.
Decision theory meets
linear optimization beyond computation.
In Alessandro Antonucci, Laurence Cholvy, and
Odile Papini, editors, Symbolic and Quantitative
Approaches to Reasoning with Uncertainty: 14th European Conference, ECSQARU
2017, Lugano, Switzerland, July 10–14, 2017, Proceedings, pages
329–339, Cham, 2017. Springer International Publishing.
- Christoph Jansen, Georg
Schollmeyer, and Thomas Augustin.
Concepts for decision
making under severe uncertainty with partial ordinal and partial cardinal
preferences.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 181–192. PMLR, 2017.
- Julia Plass, Aziz Omar, and
Thomas Augustin.
Towards a cautious
modelling of missing data in small area estimation.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 253–264. PMLR, 2017.
- Julia
Plass, Aziz Omar, and Thomas Augustin.
Towards a cautious
modelling of missing data in small area estimation.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 253–264. PMLR, 2017.
- Georg Schollmeyer.
Reliable statistical
modeling of weakly structured information: contributions to partial
identification, stochastic partial ordering and imprecise
probabilities.
PhD thesis, Department of Statistics, LMU Munich, 2017.
- Georg Schollmeyer.
On the number and
characterization of the extreme points of the core of necessity measures on
finite spaces.
In Thomas Augustin, Serena Doria,
Enrique Miranda, and Erik Quaeghebeur, editors,
ISIPTA '15, Proceedings of the Ninth International Symposium on
Imprecise Probability: Theories and Applications, pages 277–286,
Rome, 2015. Aracne.
- Georg Schollmeyer and Thomas
Augustin.
Statistical modeling under
partial identification: Distinguishing three types of identification
regions in regression analysis with interval data.
International Journal of Approximate Reasoning, 56, Part
B:224–248, 2015.
- Thomas Augustin, Frank P. A.
Coolen, Gert de Cooman, and Matthias C. M.
Troffaes, editors.
Introduction
to Imprecise Probabilities.
Wiley, Chichester, 2014.
- Thomas Augustin, Gero
Walter, and Frank P. A. Coolen.
Statistical
inference.
In Thomas Augustin, Frank P. A. Coolen,
Gert de Cooman, and Matthias C. M. Troffaes,
editors, Introduction to Imprecise Probabilities, pages
135–189. Wiley, 2014.
- Marco
Cattaneo.
A continuous updating
rule for imprecise probabilities.
In Anne Laurent, Olivier Strauss,
Bernadette Bouchon-Meunier, and Ronald Yager,
editors, Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Part 3, volume 444 of Communications
in Computer and Information Science, pages 426–435. Springer,
2014.
- Marco
Cattaneo.
Maxitive integral of
real-valued functions.
In Anne Laurent, Olivier Strauss,
Bernadette Bouchon-Meunier, and Ronald Yager,
editors, Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Part 1, volume 442 of Communications
in Computer and Information Science, pages 226–235. Springer,
2014.
- Marco Cattaneo and Andrea
Wiencierz.
On the implementation of
LIR: the case of simple linear regression with interval data.
Computational Statistics, 29(3–4):743–767, 2014.
- Marco
Cattaneo.
On maxitive integration.
Technical Report 147, Department of Statistics, LMU Munich, 2013.
- Marco
Cattaneo.
On
the robustness of imprecise probability methods.
In Fabio Cozman, Therry Denœux,
Sébastien Destercke, and Teddy Seidfenfeld,
editors, ISIPTA '13, Proceedings of the Eighth International Symposium
on Imprecise Probability: Theories and Applications, pages 33–41,
Manno, 2013. SIPTA.
- Paul
Fink and Richard Crossman.
Entropy
based classification trees.
In Fabio Cozman, Therry Denœux,
Sébastien Destercke, and Teddy Seidfenfeld,
editors, ISIPTA '13, Proceedings of the Eighth International Symposium
on Imprecise Probability: Theories and Applications, pages 139–147,
Manno, 2013. SIPTA.
- Atiye Sarabi-Jamab,
Babak Nadjar Araabi, and Thomas Augustin.
Information-based dissimilarity assessment in Dempster-Shafer theory.
Knowledge-Based Systems, 54:114–127, 2013.
- Georg Schollmeyer and Thomas
Augustin.
On
sharp identification regions for regression under interval data.
In Fabio Cozman, Therry Denœux,
Sébastien Destercke, and Teddy Seidfenfeld,
editors, ISIPTA '13, Proceedings of the Eighth International Symposium
on Imprecise Probability: Theories and Applications, pages 285–294,
Manno, 2013. SIPTA.
- Georg Schollmeyer and Thomas
Augustin.
On sharp iientification regions for regression under interval data.
Technical Report 143, Department of Statistics, LMU Munich, 2013.
- Lev Utkin and Andrea
Wiencierz.
An
imprecise boosting-like approach to regression.
In Fabio Cozman, Therry Denœux,
Sébastien Destercke, and Teddy Seidfenfeld,
editors, ISIPTA '13, Proceedings of the Eighth International Symposium
on Imprecise Probability: Theories and Applications, pages 345–354,
Manno, 2013. SIPTA.
- Alessandro Antonucci, Marco
Cattaneo, and Giorgio Corani.
Likelihood-based robust
classification with Bayesian networks.
In Salvatore Greco, Bernadette Bouchon-Meunier,
Giulianella Coletti, Mario Fedrizzi,
Benedetto Matarazzo, and Ronald Yager, editors,
Advances in Computational Intelligence, Part 3, volume 299 of
Communications in Computer and Information Science, pages
491–500. Springer, 2012.
- Marco Cattaneo and Andrea
Wiencierz.
Likelihood-based imprecise
regression.
International Journal of Approximate Reasoning, 53(8):1137–1154,
2012.
- Helmut Küchenhoff, Thomas
Augustin, and Anne Kunz.
Partially identified prevalence estimation under misclassification using the
Kappa coefficient.
International Journal of Approximate Reasoning, 53(8):1168–1182,
2012.
- Andrea Wiencierz and Marco
Cattaneo.
An exact algorithm for
likelihood-based imprecise regression in the case of simple linear regression
with interval data.
In Rudolf Kruse, Michael Berthold,
Christian Moewes, Marıa Ángeles Gil,
Przemysław Grzegorzewski, and Olgierd
Hryniewicz, editors, Synergies of Soft Computing and Statistics for
Intelligent Data Analysis, volume 190 of Advances in
Intelligent Systems and Computing, pages 293–301. Springer,
2012.
- Alessandro Antonucci, Marco
Cattaneo, and Giorgio Corani.
Likelihood-based
naive credal classifier.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
21–30, Manno, 2011. SIPTA.
- Rebecca
Baker, Pauline Coolen-Schrijner, Frank Coolen,
and Thomas Augustin.
Nonparametric
predictive inference for subcategory data.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
41–50, Manno, 2011. SIPTA.
- Marco
Cattaneo.
Belief functions
combination without the assumption of independence of the information
sources.
International Journal of Approximate Reasoning, 52(3):299–315,
2011.
- Marco Cattaneo and Andrea
Wiencierz.
Regression
with imprecise data: A robust approach.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
119–128, Manno, 2011. SIPTA.
- Marco Cattaneo and Andrea
Wiencierz.
Robust regression with
imprecise data.
Technical Report 114, Department of Statistics, LMU Munich, 2011.
- Frank Coolen, Matthias
Troffaes, and Thomas Augustin.
Imprecise
probabilities.
In Miodrag Lovric, editor, International Encyclopedia of
Statistical Science, pages 645–648. Springer, 2011.
- Richard Crossman, Joaquín
Abellán, Thomas Augustin, and Frank
Coolen.
Building
imprecise classification trees with entropy ranges.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
129–138, Manno, 2011. SIPTA.
- Daniel Fischer, Wolfgang
Bonß, Thomas Augustin, Felix Bader,
Michaela Pichlbauer, and Dominikus Vogl,
editors.
Uneindeutigkeit als Herausforderung.
Universität der Bundeswehr München, Neubiberg, 1 edition, 2011.
- Helmut Küchenhoff, Thomas
Augustin, and Anne Kunz.
Partially
identified prevalence estimation under misclassification using the Kappa
coefficient.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
237–246, Manno, 2011. SIPTA.
- Gero
Walter, Thomas Augustin, and Frank Coolen.
On
prior-data conflict in predictive Bernoulli inferences.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
391–400, Manno, 2011. SIPTA.
- Thomas Augustin and Robert
Hable.
On the impact of
robust statistics on imprecise probability models: a review.
Structural Safety, 32(6):358–365, 2010.
- Thomas Augustin, Frank
Coolen, Matthias Troffaes, and Serafín
Moral, editors.
Special issue
on imprecise probability in statistical inference and decision making.
International Journal of Approximate Reasoning, 51 (9),
1011–1172, 2010.
- Marco
Cattaneo.
Likelihood-based
inference for probabilistic graphical models: Some preliminary results.
In Petri Myllymäki, Teemu Roos, and
Tommi Jaakkola, editors, PGM 2010, Proceedings of The
Fifth European Workshop on Probabilistic Graphical Models, pages
57–64. HIIT Publications, 2010.
- Gero Walter and Thomas
Augustin.
Bayesian
linear regression — different conjugate models and their (in)sensitivity to
prior-data conflict.
In Thomas Kneib and Gerhard Tutz, editors,
Statistical Modelling and Regression Structures, Festschrift
in Honour of Ludwig Fahrmeir, pages 59–78. Springer, 2010.
- Thomas Augustin, Frank
Coolen, Pauline Coolen-Schrijner, and Matthias
Troffaes, editors.
Special issue on statistical theory and practice with Journal of
Statistical Theory and Practice 3, 1–303, 2009.
see also Coolen-Schrijner, Coolen, Troffaes, Augustin, Gupta, editors
(2009).
- Thomas Augustin, Frank
Coolen, Matthias Troffaes, and Serafín
Moral, editors.
Proceedings of
ISIPTA '09. Fifth International Symposium on Imprecise Probabilities and
Their Applications, Manno, 2009. SIPTA.
- Thomas Augustin, Enrique
Miranda, and Jirina Vejnarova, editors.
Special issue
on imprecise probability models and their applications. International
Journal of Approximate Reasoning, 50 (4), 581–694,
2009.
- Andrey Bronevich and Thomas
Augustin.
Approximation
of coherent lower probabilities by 2-monotone measures.
In Thomas Augustin, Frank Coolen,
Serafín Moral, and Matthias Troffaes,
editors, ISIPTA '09: Proceedings of the Fifth International Symposium
on Imprecise Probabilities and their Applications, pages 61–69,
Manno, 2009. SIPTA.
- Marco
Cattaneo.
A generalization
of credal networks.
In Thomas Augustin, Frank Coolen,
Serafín Moral, and Matthias Troffaes,
editors, ISIPTA '09, Proceedings of the Sixth International Symposium
on Imprecise Probability: Theories and Applications, pages 79–88,
Manno, 2009. SIPTA.
- Frank Coolen and Thomas
Augustin.
A nonparametric predictive
alternative to the imprecise Dirichlet model: the case of a known number of
categories.
International Journal of Approximate Reasoning, 50:217–230,
2009.
- Pauline Coolen-Schrijner,
Frank Coolen, Troffaes Matthias, and
Thomas Augustin.
Imprecision in statistical theory and practice.
Journal of Statistical Theory and Practice, 3:1–9, 2009.
- Jochen Einbeck and Thomas
Augustin.
On design-weighted local fitting and its relation to the Horvitz-Thompson
estimator.
Statistica Sinica, 19(1):103–123, 2009.
- Gero Walter and Thomas
Augustin.
Bayesian linear
regression — different conjugate models and their (in)sensitivity to
prior-data conflict.
Technical Report 69, Department of Statistics, LMU Munich, 2009.
- Gero Walter and Thomas
Augustin.
Imprecision and prior-data conflict in generalized Bayesian inference.
Journal of Statistical Theory and Practice, 3:255–271, 2009.
- Andrea
Wiencierz.
Arthur P. Dempster's generalized inference theory: Theoretical
foundations, extensions and modern applications.
Master's thesis, LMU Munich, 2009.
- Marco
Cattaneo.
Fuzzy probabilities
based on the likelihood function.
In Didier Dubois, Maria Lubiano,
Henri Prade, María Gil,
Przemysław Grzegorzewski, and Olgierd
Hryniewicz, editors, Soft Methods for Handling Variability and
Imprecision, volume 48 of Advances in Intelligent and Soft
Computing, pages 43–50. Springer, 2008.
- Marco
Cattaneo.
Probabilistic-possibilistic
belief networks.
Technical Report 32, Department of Statistics, LMU Munich, 2008.
- Hermann Held, Thomas
Augustin, and Elmar Kriegler.
Bayesian learning for a
class of priors with prescribed marginals.
International Journal of Approximate Reasoning, 49(1):212–233,
2008.
- Frank Coolen and Thomas
Augustin.
Multinomial
nonparametric predictive inference with sub-categories.
In Gert de Cooman, Jirina Vejnarova, and
Marco Zaffalon, editors, ISIPTA '07: Proceedings of the
Fifth International Symposium on Imprecise Probabilities and their
Applications, pages 77–86, Manno, 2007. SIPTA.
- Michael Obermeier and Thomas
Augustin.
Luceno's
discretization method and its application in decision making under
ambiguity.
In Gert de Cooman, Jirina Vejnarova, and
Marco Zaffalon, editors, ISIPTA '07: Proceedings of the
Fifth International Symposium on Imprecise Probabilities and their
Applications, pages 327–336, Manno, 2007. SIPTA.
- Lev Utkin and Thomas
Augustin.
Decision making under
imperfect measurement using the imprecise Dirichlet model.
International Journal of Approximate Reasoning, 44(3):322–338,
2007.
- Gero
Walter.
The normal regression model as a LUCK-model.
Discussion Paper, 2007.
- Gero
Walter.
Sketch of an alternative approach to linear regression analysis under sets of
conjugate priors.
Discussion Paper, 2007.
- Gero
Walter, Thomas Augustin, and Annette Peters.
Linear regression
analysis under sets of conjugate priors.
In Gert de Cooman, Jirina Vejnarova, and
Marco Zaffalon, editors, ISIPTA '07: Proceedings of the
Fifth International Symposium on Imprecise Probabilities and their
Applications, pages 445–455, Manno, 2007. SIPTA.
- Gero
Walter.
Robuste Bayes-Regression mit Mengen von Prioris — Ein Beitrag zur
Statistik unter komplexer Unsicherheit.
Master's thesis, LMU Munich, 2006.
- Thomas
Augustin.
Generalized basic
probability assignments.
International Journal of General Systems, 34(4):451–463,
2005.
- Frank Coolen and Thomas
Augustin.
Learning from
multinomial data: a nonparametric predictive alternative to the imprecise
Dirichlet model.
In Fabio Cozman, Robert Nau, and
Teddy Seidenfeld, editors, ISIPTA '05, Proceedings of
the Fourth International Symposium on Imprecise Probabilities and Their
Applications, pages 125–135, Pittsburgh, Manno, 2005. Carnegie
Mellon University, SIPTA.
- Lev Utkin and Thomas
Augustin.
Powerful
algorithms for decision making under partial prior information and general
ambiguity attitudes.
In Fabio Cozman, Robert Nau, and
Teddy Seidenfeld, editors, ISIPTA '05, Proceedings of
the Fourth International Symposium on Imprecise Probabilities and Their
Applications, pages 349–358, Pittsburgh, Manno, 2005. Carnegie
Mellon University, SIPTA.
- Thomas
Augustin.
Optimal decisions under
complex uncertainty — basic notions and a general algorithm for data-based
decision making with partial prior knowledge described by interval
probability.
ZAMM Zeitschrift für Angewandte Mathematik und Mechanik,
84(10-11):678–687, 2004.
- Thomas Augustin and Frank
Coolen.
Nonparametric predictive
inference and interval probability.
Journal of Statistical Planning and Inference, 124(2):251–272,
2004.
- Lev Utkin and Thomas
Augustin.
Fuzzy decision making using the imprecise Dirichlet model.
In Proceedings of the International Conference on Fuzzy Sets and Soft
Computing in Economics and Finance, pages 186–193, Mexican Petroleum
Institute. St. Petersburg, 2004.
- Thomas
Augustin.
On the suboptimality of
the generalized Bayes rule and robust Bayesian procedures from the
decision theoretic point of view — a cautionary note on updating imprecise
priors.
In Jean-Marc Bernard, Teddy Seidenfeld, and
Marco Zaffalon, editors, ISIPTA '03: Proceedings of the
Third International Symposium on Imprecise Probabilities and their
Applications, pages 31–45, Lugano, Waterloo, 2003. Carleton
Scientific.
- Lev Utkin and Thomas
Augustin.
Decision making with
imprecise second order probabilities.
In Jean-Marc Bernard, Teddy Seidenfeld, and
Marco Zaffalon, editors, ISIPTA '03: Proceedings of the
Third International Symposium on Imprecise Probabilities and their
Applications, pages 547–561, Lugano, Waterloo, 2003. Carleton
Scientific.
- Lev Utkin and Thomas
Augustin.
Risk analysis on the basis of partial information about quantiles.
In Solojentsev Evgueni, editor, Modelling and Analysis of
Safety and Risk in Complex Systems (Proceedings of the Third International
Scientific School MA SR 2003), pages 172–178, St. Petersburg, 2003.
Institute of Problems of Mechanical Engineering of Russian Academy of Science
(IMPE RAS).
- Kurt Weichselberger and Thomas
Augustin.
On the symbiosis of two
concepts of conditional interval probability.
In Jean-Marc Bernard, Teddy Seidenfeld, and
Marco Zaffalon, editors, ISIPTA '03: Proceedings of the
Third International Symposium on Imprecise Probabilities and their
Applications, pages 547–561. Carleton Scientific, Lugano, Waterloo,
2003.
- Thomas
Augustin.
Expected utility within a
generalized concept of probability: a comprehensive framework for decision
making under ambiguity.
Statistical Papers, 43(1):5–22, 2002.
- Thomas
Augustin.
Neyman-Pearson
testing under interval probability by globally least favorable pairs
reviewing Huber-Strassen theory and extending it to general interval
probability.
Journal of Statistical Planning and Inference, 105(1):149–173,
2002.
- Thomas
Augustin.
On decision making
under ambiguous prior and sampling information.
In Gert de Cooman, Terrence Fine,
Serafín Moral, and Teddy Seidenfeld,
editors, ISIPTA '01: Proceedings of the Second International Symposium
on Imprecise Probabilities and their Applications, pages 9–16,
Ithaca (N.Y.), Shaker, Maastricht, 2001. Cornell University.
- Sigrid Pöhlmann and Thomas
Augustin.
A Kiefer-Weiss optimal sequential sign test — Some considerations on a
bioequivalence problem from the viewpoint of quality management.
In Joachim Kunert and Götz Trenkler, editors,
Mathematical Statistics with Applications in Biometry (Festschrift for
Siegfried Schach), pages 179–188. Josef Eul, Köln, 2001.
- Kurt Weichselberger.
Elementare Grundbegriffe einer allgemeineren
Wahrscheinlichkeitsrechnung I — Intervallwahrscheinlichkeit als
umfassendes Konzept.
Physika, Heidelberg, 2001.
(unter Mitarbeit von T. Augustin und A. Wallner), Seiten: 684 + xiv.
- Thomas Augustin.
Globally
least favorable pairs and Neyman-Pearson testing under interval
probability.
In Gert de Cooman, Fabio Gagliardi Cozman,
Serafín Moral, and Peter Walley, editors,
ISIPTA '99: Proceedings of the First International Symposium on
Imprecise Probabilities and their Applications, pages 15–24, Gent,
1999.
- Thomas Augustin.
On data-based checking of hypotheses in the presence of uncertain knowledge.
In Wolfang Gaul and Hermann Locarek-Junge,
editors, Classification in the Information Age, pages
127–135. Springer, 1999.
- Thomas
Augustin.
Optimale Tests bei Intervallwahrscheinlichkeit.
Vandenhoeck and Ruprecht, Göttingen, 1998.
With a preface by Kurt Weichselberger, Pages: 290 + XIV.
- Kurt Weichselberger and Thomas
Augustin.
Analysing Ellsberg's paradox by means of interval-probability.
In Robert Galata and Helmut Küchenhoff,
editors, Econometrics in Theory and Practice, pages 291–304.
Physica, Heidelberg, 1998.
- Thomas
Augustin.
Modeling weak information with generalized probability assignments.
In Hans-Hermann Bock and Wolfgang Polasek,
editors, Data Analysis and Information Systems. Statistical and
Conceptual Approaches, pages 101–113. Springer, Heidelberg,
1996.
nach oben
Entscheidungstheorie
- Patrick Schwaferts and Thomas
Augustin.
Imprecise
hypothesis-based Bayesian decision making with simple hypotheses.
In Jasper De Bock, Cassio P. de Campos,
Gert de Cooman, Erik Quaeghebeur, and
Gregory Wheeler, editors, Proceedings of the Eleventh
International Symposium on Imprecise Probability: Theories and
Applications, volume 103 of Proceedings of Machine Learning
Research, pages 338–345. PMLR, 2019.
(PDF)
- Christoph
Jansen.
Some contributions to
decision making in complex information settings with imprecise probabilities
and incomplete preferences: Theoretical and algorithmic results.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Christoph Jansen, Georg
Schollmeyer, and Thomas Augustin.
Concepts for decision
making under severe uncertainty with partial ordinal and partial cardinal
preferences.
International Journal of Approximate Reasoning, 98:112–131, 2018.
Substantially extended, invited special issue version of Jansen, Schollmeyer &
Augustin (2017, ISIPTA).
- Christoph Jansen, Georg
Schollmeyer, and Thomas Augustin.
A probabilistic
evaluation framework for preference aggregation reflecting group
homogeneity.
Mathematical Social Sciences, 96:49–62, 2018.
- Christoph Jansen, Thomas
Augustin, and Georg Schollmeyer.
Decision theory meets
linear optimization beyond computation.
In Alessandro Antonucci, Laurence Cholvy, and
Odile Papini, editors, Symbolic and Quantitative
Approaches to Reasoning with Uncertainty: 14th European Conference, ECSQARU
2017, Lugano, Switzerland, July 10–14, 2017, Proceedings, pages
329–339, Cham, 2017. Springer International Publishing.
- Christoph Jansen, Georg
Schollmeyer, and Thomas Augustin.
Concepts for decision
making under severe uncertainty with partial ordinal and partial cardinal
preferences.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 181–192. PMLR, 2017.
- Marco
Cattaneo.
Maxitive integral of
real-valued functions.
In Anne Laurent, Olivier Strauss,
Bernadette Bouchon-Meunier, and Ronald Yager,
editors, Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Part 1, volume 442 of Communications
in Computer and Information Science, pages 226–235. Springer,
2014.
- Christoph Bernau, Thomas
Augustin, and Anne-Laure Boulesteix.
Correcting the optimal
resampling-based error rate by estimating the error rate of wrapper
algorithms.
Biometrics, 69(3):693–702, 2013.
- Marco
Cattaneo.
Likelihood decision functions.
Electronic Journal of Statistics, 7:2924–2946, 2013.
- Christoph Bernau, Thomas
Augustin, and Anne-Laure Boulesteix.
Correcting the optimally
selected resampling-based error rate: A smooth analytical alternative to
nested cross-validation.
Technical Report 105, Department of Statistics, LMU, 2011.
- Daniel Fischer, Wolfgang
Bonß, Thomas Augustin, Felix Bader,
Michaela Pichlbauer, and Dominikus Vogl,
editors.
Uneindeutigkeit als Herausforderung.
Universität der Bundeswehr München, Neubiberg, 1 edition, 2011.
- Andrey Bronevich and Thomas
Augustin.
Approximation
of coherent lower probabilities by 2-monotone measures.
In Thomas Augustin, Frank Coolen,
Serafín Moral, and Matthias Troffaes,
editors, ISIPTA '09: Proceedings of the Fifth International Symposium
on Imprecise Probabilities and their Applications, pages 61–69,
Manno, 2009. SIPTA.
- Andreas Mihalyi, Barbara
Deml, and Thomas Augustin.
A contribution to
integrated driver modeling: a coherent framework for modeling both
non-routine and routine elements of the driving task.
In Vincent Duffy, editor, 2nd International Conference on
Digital Human Modeling held at the HCI International (13th International
Conference on Human-Computer Interaction), pages 433–442. Springer,
2009.
- Michael Obermeier and Thomas
Augustin.
Luceno's
discretization method and its application in decision making under
ambiguity.
In Gert de Cooman, Jirina Vejnarova, and
Marco Zaffalon, editors, ISIPTA '07: Proceedings of the
Fifth International Symposium on Imprecise Probabilities and their
Applications, pages 327–336, Manno, 2007. SIPTA.
- Lev Utkin and Thomas
Augustin.
Decision making under
imperfect measurement using the imprecise Dirichlet model.
International Journal of Approximate Reasoning, 44(3):322–338,
2007.
- Lev Utkin and Thomas
Augustin.
Powerful
algorithms for decision making under partial prior information and general
ambiguity attitudes.
In Fabio Cozman, Robert Nau, and
Teddy Seidenfeld, editors, ISIPTA '05, Proceedings of
the Fourth International Symposium on Imprecise Probabilities and Their
Applications, pages 349–358, Pittsburgh, Manno, 2005. Carnegie
Mellon University, SIPTA.
- Thomas
Augustin.
An exact corrected
log-likelihood function for Cox's proportional hazards model under
measurement error and some extensions.
Scandinavian Journal of Statistics, 31(1):43–50, 2004.
- Thomas
Augustin.
Optimal decisions under
complex uncertainty — basic notions and a general algorithm for data-based
decision making with partial prior knowledge described by interval
probability.
ZAMM Zeitschrift für Angewandte Mathematik und Mechanik,
84(10-11):678–687, 2004.
- Lev Utkin and Thomas
Augustin.
Fuzzy decision making using the imprecise Dirichlet model.
In Proceedings of the International Conference on Fuzzy Sets and Soft
Computing in Economics and Finance, pages 186–193, Mexican Petroleum
Institute. St. Petersburg, 2004.
- Thomas
Augustin.
On the suboptimality of
the generalized Bayes rule and robust Bayesian procedures from the
decision theoretic point of view — a cautionary note on updating imprecise
priors.
In Jean-Marc Bernard, Teddy Seidenfeld, and
Marco Zaffalon, editors, ISIPTA '03: Proceedings of the
Third International Symposium on Imprecise Probabilities and their
Applications, pages 31–45, Lugano, Waterloo, 2003. Carleton
Scientific.
- Lev Utkin and Thomas
Augustin.
Decision making with
imprecise second order probabilities.
In Jean-Marc Bernard, Teddy Seidenfeld, and
Marco Zaffalon, editors, ISIPTA '03: Proceedings of the
Third International Symposium on Imprecise Probabilities and their
Applications, pages 547–561, Lugano, Waterloo, 2003. Carleton
Scientific.
- Lev Utkin and Thomas
Augustin.
Risk analysis on the basis of partial information about quantiles.
In Solojentsev Evgueni, editor, Modelling and Analysis of
Safety and Risk in Complex Systems (Proceedings of the Third International
Scientific School MA SR 2003), pages 172–178, St. Petersburg, 2003.
Institute of Problems of Mechanical Engineering of Russian Academy of Science
(IMPE RAS).
- Thomas
Augustin.
Expected utility within a
generalized concept of probability: a comprehensive framework for decision
making under ambiguity.
Statistical Papers, 43(1):5–22, 2002.
- Thomas
Augustin.
On decision making
under ambiguous prior and sampling information.
In Gert de Cooman, Terrence Fine,
Serafín Moral, and Teddy Seidenfeld,
editors, ISIPTA '01: Proceedings of the Second International Symposium
on Imprecise Probabilities and their Applications, pages 9–16,
Ithaca (N.Y.), Shaker, Maastricht, 2001. Cornell University.
- Kurt Weichselberger and Thomas
Augustin.
Analysing Ellsberg's paradox by means of interval-probability.
In Robert Galata and Helmut Küchenhoff,
editors, Econometrics in Theory and Practice, pages 291–304.
Physica, Heidelberg, 1998.
nach oben
Partielle Identifikation
- Eva Endres, Paul Fink, and
Thomas Augustin.
Imprecise imputation: A
nonparametric micro approach reflecting the natural uncertainty of
statistical matching with categorical data.
Journal of Official Statistical, 35:599–624, 2019.
- Julia Plass, Marco Cattaneo,
Thomas Augustin, Georg Schollmeyer, and
Christian Heumann.
Reliable inference in categorical
regression analysis for non-randomly coarsened observations.
International Statistical Review, 87:580–603, 2019.
- Eva Endres, Paul Fink, and
Thomas Augustin.
Imprecise imputation: A
nonparametric micro approach reflecting the natural uncertainty of
statistical matching with categorical data.
Technical Report 214, Department of Statistics, LMU Munich, 2018.
- Paul Fink.
Contributions to
reasoning on imprecise data: Imprecise classification trees, generalized
linear regression on microaggregated data and imprecise
imputation.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Paul
Fink and Thomas Augustin.
(Generalized) linear
regression on microaggregated data – from nuisance parameter optimization to
partial identification.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 157–168. PMLR, 2017.
- Julia Plass, Marco Cattaneo,
Thomas Augustin, Georg Schollmeyer, and
Christian Heumann.
Towards a reliable categorical
regression analysis for non-randomly coarsened observations: An analysis with
German labour market data.
Technical Report 206, Department of Statistics, LMU Munich, 2017.
- Julia Plass, Marco Cattaneo,
Georg Schollmeyer, and Thomas Augustin.
On the testability of
coarsening assumptions: A hypothesis test for subgroup independence.
International Journal of Approximate Reasoning, 90:292–306,
2017.
- Julia Plass, Marco Cattaneo,
Georg Schollmeyer, and Thomas Augustin.
On the testability of
coarsening assumptions: A hypothesis test for subgroup independence.
Technical Report 201, Department of Statistics, LMU Munich, 2017.
- Julia Plass, Aziz Omar, and
Thomas Augustin.
Towards a cautious
modelling of missing data in small area estimation.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 253–264. PMLR, 2017.
- Julia
Plass, Aziz Omar, and Thomas Augustin.
Towards a cautious
modelling of missing data in small area estimation.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 253–264. PMLR, 2017.
- Georg Schollmeyer.
Reliable statistical
modeling of weakly structured information: contributions to partial
identification, stochastic partial ordering and imprecise
probabilities.
PhD thesis, Department of Statistics, LMU Munich, 2017.
- Julia Plass, Marco Cattaneo,
Georg Schollmeyer, and Thomas Augustin.
Testing of coarsening
mechanisms: Coarsening at random versus subgroup independence.
In Maria Brigida Ferraro, Paolo Giordani,
Barbara Vantaggi, Marek Gagolewski,
María Ángeles Gil, Przemysław
Grzegorzewski, and Olgierd Hryniewicz, editors, Soft
Methods for Data Science, pages 415–422. Springer, SMPS, 2016.
- Julia Plass, Thomas Augustin,
Marco Cattaneo, and Georg Schollmeyer.
Statistical modelling
under epistemic data imprecision: Some results on estimating multinomial
distributions and logistic regression for coarse categorical data.
In Thomas Augustin, Serena Doria,
Enrique Miranda, and Erik Quaeghebeur, editors,
ISIPTA '15, Proceedings of the Ninth International Symposium on
Imprecise Probability: Theories and Applications, pages 247–256,
Rome, 2015. Aracne.
- Georg Schollmeyer and Thomas
Augustin.
Statistical modeling under
partial identification: Distinguishing three types of identification
regions in regression analysis with interval data.
International Journal of Approximate Reasoning, 56, Part
B:224–248, 2015.
- Julia
Plaß.
Coarse categorical data under epistemic and ontologic uncertainty: Comparison
and extension of some approaches.
Master's thesis, LMU Munich, 2013.
- Georg Schollmeyer and Thomas
Augustin.
On
sharp identification regions for regression under interval data.
In Fabio Cozman, Therry Denœux,
Sébastien Destercke, and Teddy Seidfenfeld,
editors, ISIPTA '13, Proceedings of the Eighth International Symposium
on Imprecise Probability: Theories and Applications, pages 285–294,
Manno, 2013. SIPTA.
- Georg Schollmeyer and Thomas
Augustin.
On sharp iientification regions for regression under interval data.
Technical Report 143, Department of Statistics, LMU Munich, 2013.
nach oben
Grundlagen der Wahrscheinlichkeit, Konzepte von Unsicherheit
- Aziz Omar and Thomas
Augustin.
Estimation of
classification probabilities in small domains accounting for nonresponse
relying on imprecise probability.
International Journal of Approximate Reasoning, 115:134–143,
2019.
Substantially extended, invited special issue version of Omar & Augustin
(2018, SMPS).
- Thomas Augustin.
Imprecise
sampling models for modelling unobserved heterogeneity? Basic ideas of a
credal likelihood concept.
In Davide Ciucci, Gabriella Pasi, and
Barbara Vantaggi, editors, Scalable Uncertainty
Management (Proceedings of the 12th International Conference, SUM 2018, Milan
(Italy), volume 11 of Lecture Notes in Artificial
Intelligence, pages 351–358. Springer, 2018.
- Christoph
Jansen.
Some contributions to
decision making in complex information settings with imprecise probabilities
and incomplete preferences: Theoretical and algorithmic results.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Aziz Omar and Thomas
Augustin.
Estimation
of classification probabilities in small domains accounting for nonresponse
relying on imprecise probability.
In Sebastien Destercke, Thierry Denoeux,
Maria Angeles Gil, Przemyslaw Grzegorzewski,
and Olgierd Hryniewicz, editors, SMPS 2018: Uncertainty
Modelling in Data Science, volume 832 of Advances in Intelligent
Systems and Computing, pages 175–182. Springer, 2018.
- Julia Plass.
Statistical modelling of
categorical data under ontic and epistemic imprecision: contributions to
power set based analyses, cautious likelihood inference and (non-)testability
of coarsening mechanism.
PhD thesis, Department of Statistics, LMU Munich, 2018.
- Thomas Augustin and Rudolf
Seising.
Kurt
Weichselberger's contribution to imprecise probabilities.
In Alessandro Antonucci, Giorgio Corani,
Inés Couso, and Sébastien Destercke,
editors, Proceedings of the Tenth International Symposium on Imprecise
Probability: Theories and Applications, volume 62 of Proceedings
of Machine Learning Research, pages 13–24. PMLR, 2017.
- Thomas Augustin, Frank P. A.
Coolen, Gert de Cooman, and Matthias C. M.
Troffaes, editors.
Introduction
to Imprecise Probabilities.
Wiley, Chichester, 2014.
- Thomas Augustin, Gero
Walter, and Frank P. A. Coolen.
Statistical
inference.
In Thomas Augustin, Frank P. A. Coolen,
Gert de Cooman, and Matthias C. M. Troffaes,
editors, Introduction to Imprecise Probabilities, pages
135–189. Wiley, 2014.
- Marco
Cattaneo.
A continuous updating
rule for imprecise probabilities.
In Anne Laurent, Olivier Strauss,
Bernadette Bouchon-Meunier, and Ronald Yager,
editors, Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Part 3, volume 444 of Communications
in Computer and Information Science, pages 426–435. Springer,
2014.
- Marco
Cattaneo.
Maxitive integral of
real-valued functions.
In Anne Laurent, Olivier Strauss,
Bernadette Bouchon-Meunier, and Ronald Yager,
editors, Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Part 1, volume 442 of Communications
in Computer and Information Science, pages 226–235. Springer,
2014.
- Marco
Cattaneo.
Likelihood decision functions.
Electronic Journal of Statistics, 7:2924–2946, 2013.
- Marco
Cattaneo.
On maxitive integration.
Technical Report 147, Department of Statistics, LMU Munich, 2013.
- Marco
Cattaneo.
On
the robustness of imprecise probability methods.
In Fabio Cozman, Therry Denœux,
Sébastien Destercke, and Teddy Seidfenfeld,
editors, ISIPTA '13, Proceedings of the Eighth International Symposium
on Imprecise Probability: Theories and Applications, pages 33–41,
Manno, 2013. SIPTA.
- Atiye Sarabi-Jamab,
Babak Nadjar Araabi, and Thomas Augustin.
Information-based dissimilarity assessment in Dempster-Shafer theory.
Knowledge-Based Systems, 54:114–127, 2013.
- Marco
Cattaneo.
Likelihood decision
functions.
Technical Report 128, Department of Statistics, LMU Munich, 2012.
- Thomas Augustin and Marco
Cattaneo.
Foundations of
probability.
In Miodrag Lovric, editor, International Encyclopedia of
Statistical Science, pages 542–544. Springer, 2011.
- Marco
Cattaneo.
Belief functions
combination without the assumption of independence of the information
sources.
International Journal of Approximate Reasoning, 52(3):299–315,
2011.
- Marco
Cattaneo.
Probabilistic-possibilistic belief networks.
In Angel Marchev, Angel Angelov,
Margarita Harizanova, Milcho Mirchev,
Matilda Alexandrova, Maya Lambovska, and
Vasil Alexandria, editors, Vanguard Scientific
Instruments in Management 2009 (VSIM:09), volume 2, pages 59–72.
VSIM, 2010.
- Marco
Cattaneo.
Fuzzy probabilities
based on the likelihood function.
In Didier Dubois, Maria Lubiano,
Henri Prade, María Gil,
Przemysław Grzegorzewski, and Olgierd
Hryniewicz, editors, Soft Methods for Handling Variability and
Imprecision, volume 48 of Advances in Intelligent and Soft
Computing, pages 43–50. Springer, 2008.
- Marco
Cattaneo.
Probabilistic-possibilistic
belief networks.
Technical Report 32, Department of Statistics, LMU Munich, 2008.
nach oben
Inferenz-Theorie
- Luisa
Ebner, Patrick Schwaferts, and Thomas
Augustin.
Robust Bayes factor
for independent two-sample comparisons under imprecise prior information.
In Jasper De Bock, Cassio P. de Campos,
Gert de Cooman, Erik Quaeghebeur, and
Gregory Wheeler, editors, Proceedings of the Eleventh
International Symposium on Imprecise Probability: Theories and
Applications, volume 103 of Proceedings of Machine Learning
Research, pages 167–174. PMLR, 2019.
(PDF)
- Thomas Augustin and Rudolf
Seising.
Kurt Weichselberger's
contribution to imprecise probabilities.
International Journal of Approximate Reasoning, 98:132–145, 2018.
Substantially extended, invited special issue version of Augustin & Seising
(2017, ISIPTA).
- Thomas Augustin, Gero Walter,
and Frank P. A. Coolen.
Statistical
inference.
In Thomas Augustin, Frank P. A. Coolen,
Gert de Cooman, and Matthias C. M. Troffaes,
editors, Introduction to Imprecise Probabilities, pages
135–189. Wiley, 2014.
- Marco
Cattaneo.
A continuous updating
rule for imprecise probabilities.
In Anne Laurent, Olivier Strauss,
Bernadette Bouchon-Meunier, and Ronald Yager,
editors, Information Processing and Management of Uncertainty in
Knowledge-Based Systems, Part 3, volume 444 of Communications
in Computer and Information Science, pages 426–435. Springer,
2014.
- Marco Cattaneo and Andrea
Wiencierz.
On the implementation of
LIR: the case of simple linear regression with interval data.
Computational Statistics, 29(3–4):743–767, 2014.
- Christoph Bernau, Thomas
Augustin, and Anne-Laure Boulesteix.
Correcting the optimal
resampling-based error rate by estimating the error rate of wrapper
algorithms.
Biometrics, 69(3):693–702, 2013.
- Marco
Cattaneo.
Likelihood decision functions.
Electronic Journal of Statistics, 7:2924–2946, 2013.
- Alessandro Antonucci, Marco
Cattaneo, and Giorgio Corani.
Likelihood-based robust
classification with Bayesian networks.
In Salvatore Greco, Bernadette Bouchon-Meunier,
Giulianella Coletti, Mario Fedrizzi,
Benedetto Matarazzo, and Ronald Yager, editors,
Advances in Computational Intelligence, Part 3, volume 299 of
Communications in Computer and Information Science, pages
491–500. Springer, 2012.
- Marco Cattaneo and Andrea
Wiencierz.
Likelihood-based imprecise
regression.
International Journal of Approximate Reasoning, 53(8):1137–1154,
2012.
- Andrea Wiencierz and Marco
Cattaneo.
An exact algorithm for
likelihood-based imprecise regression in the case of simple linear regression
with interval data.
In Rudolf Kruse, Michael Berthold,
Christian Moewes, Marıa Ángeles Gil,
Przemysław Grzegorzewski, and Olgierd
Hryniewicz, editors, Synergies of Soft Computing and Statistics for
Intelligent Data Analysis, volume 190 of Advances in
Intelligent Systems and Computing, pages 293–301. Springer,
2012.
- Alessandro Antonucci, Marco
Cattaneo, and Giorgio Corani.
Likelihood-based
naive credal classifier.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
21–30, Manno, 2011. SIPTA.
- Christoph Bernau, Thomas
Augustin, and Anne-Laure Boulesteix.
Correcting the optimally
selected resampling-based error rate: A smooth analytical alternative to
nested cross-validation.
Technical Report 105, Department of Statistics, LMU, 2011.
- Marco Cattaneo and Andrea
Wiencierz.
Regression
with imprecise data: A robust approach.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
119–128, Manno, 2011. SIPTA.
- Marco Cattaneo and Andrea
Wiencierz.
Robust regression with
imprecise data.
Technical Report 114, Department of Statistics, LMU Munich, 2011.
- Daniel Fischer, Wolfgang
Bonß, Thomas Augustin, Felix Bader,
Michaela Pichlbauer, and Dominikus Vogl,
editors.
Uneindeutigkeit als Herausforderung.
Universität der Bundeswehr München, Neubiberg, 1 edition, 2011.
- Gero
Walter, Thomas Augustin, and Frank Coolen.
On
prior-data conflict in predictive Bernoulli inferences.
In Frank Coolen, Gert de Cooman,
Thomas Fetz, and Michael Oberguggenberger,
editors, ISIPTA '11, Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and Applications, pages
391–400, Manno, 2011. SIPTA.
- Marco
Cattaneo.
Likelihood-based
inference for probabilistic graphical models: Some preliminary results.
In Petri Myllymäki, Teemu Roos, and
Tommi Jaakkola, editors, PGM 2010, Proceedings of The
Fifth European Workshop on Probabilistic Graphical Models, pages
57–64. HIIT Publications, 2010.
- Gero Walter and Thomas
Augustin.
Bayesian
linear regression — different conjugate models and their (in)sensitivity to
prior-data conflict.
In Thomas Kneib and Gerhard Tutz, editors,
Statistical Modelling and Regression Structures, Festschrift
in Honour of Ludwig Fahrmeir, pages 59–78. Springer, 2010.
- Gero Walter and Thomas
Augustin.
Bayesian linear
regression — different conjugate models and their (in)sensitivity to
prior-data conflict.
Technical Report 69, Department of Statistics, LMU Munich, 2009.
- Gero Walter and Thomas
Augustin.
Imprecision and prior-data conflict in generalized Bayesian inference.
Journal of Statistical Theory and Practice, 3:255–271, 2009.
- Andrea
Wiencierz.
Arthur P. Dempster's generalized inference theory: Theoretical
foundations, extensions and modern applications.
Master's thesis, LMU Munich, 2009.
- Gero
Walter.
The normal regression model as a LUCK-model.
Discussion Paper, 2007.
- Gero
Walter.
Sketch of an alternative approach to linear regression analysis under sets of
conjugate priors.
Discussion Paper, 2007.
- Gero
Walter, Thomas Augustin, and Annette Peters.
Linear regression
analysis under sets of conjugate priors.
In Gert de Cooman, Jirina Vejnarova, and
Marco Zaffalon, editors, ISIPTA '07: Proceedings of the
Fifth International Symposium on Imprecise Probabilities and their
Applications, pages 445–455, Manno, 2007. SIPTA.
- Gero
Walter.
Robuste Bayes-Regression mit Mengen von Prioris — Ein Beitrag zur
Statistik unter komplexer Unsicherheit.
Master's thesis, LMU Munich, 2006.
