SMPS 2012 - 6th International Conference on Soft Methods in Probability and Statistics

Over the last thirty years there has been a growing interest in extending the theory of probability and statistics to allow for more flexible modeling of imprecision, uncertainty, vagueness and ignorance. Most such extensions result in a "softening" of the classical theory, permitting imprecision in probability judgements, and incorporating fuzzy constraints and events. Many approaches utilise concepts, tools and techniques developed in theories such as fuzzy set theory, possibility theory, imprecise probability theory and Dempster-Shafer theory.

The need for soft extensions of probability theory is becoming apparent in a wide range of application areas. For example, in data analysis and data mining it is becoming increasingly clear that integrating fuzzy sets and probability can lead to more robust and interpretable models that better capture all the information contained in the given data. Also, in science and engineering the need to analyse and model the true uncertainty associated with complex systems requires a more sophisticated representation of ignorance than that provided by uninformative Bayesian priors.

Soft Methods in Probability and Statistics (SMPS) 2012 will be organized by both the University of Konstanz and the University of Magdeburg in Germany. It will be held in the facilities of the University of Konstanz in Konstanz (see venue). This is the sixth of a series of biennial conferences, starting in 2002.

The aim of SMPS 2012 is to serve as a forum for discussing new trends that enlarge the statistical and uncertainty modeling traditions towards the handling of incomplete, subjective or fuzzy information.

Topics

SMPS 2012 invites submissions of papers dealing with a variety of topics in soft methods in probability and statistics, which include, but are not limited to:

Analysis of Censored/Incomplete/Fuzzy Data

Analysis of Fuzzy Data

Random Sets

Fuzzy Random Variables/Random Fuzzy Sets

Fuzzy Regression Methods

Triangular Norms and Copulas

Imprecise Probabilities

Dempster-Shafer Theory

Robust Methods

Clustering and Classification

Graphical Models

Machine Learning

Heuristic Optimization

Soft Computing and Statistics

Statistical Software for Imprecise Data

Applications in Biology, Economics etc