Skiadas C.H. (ed.) Advances in Data Analysis. Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks

Birkhäuser, 2010, -368 p.This book contains the main part of the invited papers presented at the Twelfth International Conference on Applied Stochastic Models and Data Analysis (ASMDA), which took place in Chania, Crete, Greece, May 29–June 1, 2007. ASMDA, since 1981, aims at serving as the interface between stochastic modeling and data analysis and their real-life applications.
We include both theoretical and practical papers, presenting new results having the potential for solving real-life problems. An important objective was to select material presenting new methods for solving these problems by analyzing relevant data and leading to the advancement of related fields.
This book contains chapters on various important topics of data analysis such as: Data Mining and Text Mining, Asymptotic Behaviour of Stochastic Processes and Random Fields, Bioinformatics and Markov Chains, Life Table Data, Survival Analysis and Risk in Household Insurance, Neural Networks and Self-Organizing Maps, Parametric and Nonparametric Statistics, and Statistical Theory and Methods.Part I Data Mining and Text Mining
Assessing the Stability of Supplementary Elements on Principal Axes Maps Through Bootstrap Resampling. Contribution to Interpretation in Textual Analysis
A Doubly Projected Analysis for Lexical Tables
Analysis of a Mixture of Closed and Open-Ended Questions in the Case of a Multilingual Survey
Number of Frequent Patterns in Random Databases
Part II Information Theory and Statistical ApplicationsMeasures of Divergence in Model Selection
High Leverage Points and Outliers in Generalized Linear Models for Ordinal Data
On a Minimization Problem Involving Divergences
and Its Applications
Part III Asymptotic Behaviour of Stochastic Processes and Random Fields
Remarks on Stochastic Models Under Consideration
New Invariance Principles for Critical Branching Process in Random Environment
Gaussian Approximation for Multichannel Queueing Systems
Stochastic Insurance Models, Their Optimality and Stability
Central Limit Theorem for Random Fields and Applications
A Berry–Esseen Type Estimate for Dependent Systems on Transitive Graphs
Critical and Subcritical Branching Symmetric Random Walks on d-Dimensional Lattices
Part IV Bioinformatics and Markov Chains
Finite Markov Chain Embedding for the Exact Distribution of Patterns in a Set of Random Sequences
On the Convergence of the Discrete-Time Homogeneous Markov Chain
Part V Life Table Data, Survival Analysis, and Risk in Household Insurance
Comparing the Gompertz-Type Models with a First Passage Time Density Model
A Comparison of Recent Procedures in Weibull Mixture Testing
Hierarchical Bayesian Modeling of Geographic Dependence of Risk in Household Insurance
Part VI Neural Networks and Self-Organizing Maps
The FCN Framework: Development and Applications
On the Use of Self-Organising Maps to Analyze Spectral Data
Neuro-Fuzzy Versus Traditional Models for Forecasting Wind Energy Production
Part VII Parametric and Nonparametric Statistics
Nonparametric Comparison of Several Sequential k-out-of-n Systems
Adjusting p-Values when n Is Large in the Presence of Nuisance Parameters
Part VIII Statistical Theory and Methods
Fitting Pareto II Distributions on Firm Size: Statistical Methodology and Economic Puzzles
Application of Extreme Value Theory to Economic Capital Estimation
Multiresponse Robust Engineering: Industrial Experiment Parameter Estimation
Inference for Binomial Change Point Data