# Soft Methods for Data Science

## Book Description

This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy).

The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.

### Table of Contents

Chapter 1. Mean Value and Variance of Fuzzy Numbers with Non-continuous Membership Functions

Chapter 2. On the Construction of Radially Symmetric Trivariate Copulas

Chapter 3. Simulation of the Night Shift Solid Waste Collection System of Phuket Municipality

Chapter 4. Updating Context in the Equation: An Experimental Argument with Eye Tracking

Chapter 5. Black-Litterman Model with Multiple Experts' Linguistic Views

Chapter 6. Representing Lightweight Ontologies in a Product-Based Possibility Theory Framework

Chapter 7. Asymptotics of Predictive Distributions

Chapter 8. Independent k-Sample Equality Distribution Test Based on the Fuzzy Representation

Chapter 9. Agglomerative Fuzzy Clustering

Chapter 10. Bayesian Inference for a Finite Population Total Using Linked Data

Chapter 11. The Extension of Imprecise Probabilities Based on Generalized Credal Sets

Chapter 12. A Generalized SMART Fuzzy Disjunction of Volatility Indicators Applied to Option Pricing in a Binomial Model

Chapter 13. The Representation of Conglomerative Functionals

Chapter 14. The Likelihood Interpretation of Fuzzy Data

Chapter 15. Combining the Information of Multiple Ranker in Ranked Set Sampling with Fuzzy Set Approach

Chapter 16. A Savage-Like Representation Theorem for Preferences on Multi-acts

Chapter 17. On Some Functional Characterizations of (Fuzzy) Set-Valued Random Elements

Chapter 18. Maximum Likelihood Under Incomplete Information: Toward a Comparison of Criteria

Chapter 19. The Use of Uncertainty to Choose Matching Variables in Statistical Matching

Chapter 20. Beyond Fuzzy, Possibilistic and Rough: An Investigation of Belief Functions in Clustering

Chapter 21. Small Area Estimation in the Presence of Linkage Errors

Chapter 22. A Test for Truncation Invariant Dependence

Chapter 23. Finite Mixture of Linear Regression Models: An Adaptive Constrained Approach to Maximum Likelihood Estimation

Chapter 24. A Multivariate Analysis of Tourists' Spending Behaviour

Chapter 25. Robust Fuzzy Clustering via Trimming and Constraints

Chapter 26. One-Factor Lévy-Frailty Copulas with Inhomogeneous Trigger Rates

Chapter 27. A Perceptron Classifier and Corresponding Probabilities

Chapter 28. Fuzzy Signals Fed to Gaussian Channels

Chapter 29. Fuzzy Clustering Through Robust Factor Analyzers

Chapter 30. Consensus-Based Clustering in Numerical Decision-Making

Chapter 31. Spatial Outlier Detection Using GAMs and Geographical Information Systems

Chapter 32. Centering and Compound Conditionals Under Coherence

Chapter 33. Approximate Bayesian Methods for Multivariate and Conditional Copulae

Chapter 34. The Sign Test for Interval-Valued Data

Chapter 35. Probability Distributions Related to Fuzzy P-Values

Chapter 36. Probabilistic Semantics and Pragmatics for the Language of Uncertainty

Chapter 37. Dynamic Analysis of the Development of Scientific Communities in the Field of Soft Computing

Chapter 38. Talk to Your Neighbour: A Belief Propagation Approach to Data Fusion

Chapter 39. The Qualitative Characteristics of Combining Evidence with Discounting

Chapter 40. Measuring the Dissimilarity Between the Distributions of Two Random Fuzzy Numbers

Chapter 41. An Empirical Analysis of the Coherence Between Fuzzy Rating Scale- and Likert Scale-Based Responses to Questionnaires

Chapter 42. Asymptotic Results for Sums of Independent Random Variables with Alternating Laws

Chapter 43. Dispersion Measures and Multidistances on mathbbRk

Chapter 44. Full Conglomerability, Continuity and Marginal Extension

Chapter 45. On Extreme Points of p-Boxes and Belief Functions

Chapter 46. Modelling the Dependence in Multivariate Longitudinal Data by Pair Copula Decomposition

Chapter 47. Predictability in Probabilistic Discrete Event Systems

Chapter 48. A Sandwich Theorem for Natural Extensions

Chapter 49. Envelopes of Joint Probabilities with Given Marginals Under Absolute Continuity or Equivalence Constraints

Chapter 50. Square of Opposition Under Coherence

Chapter 51. Testing of Coarsening Mechanisms: Coarsening at Random Versus Subgroup Independence

Chapter 52. Two-Sample Similarity Test for the Expected Value of Random Intervals

Chapter 53. Handling Uncertainty in Structural Equation Modeling

Chapter 54. Detecting Inconsistencies in Revision Problems

Chapter 55. Tukey's Biweight Loss Function for Fuzzy Set-Valued M-estimators of Location

Chapter 56. Technical Gestures Recognition by Set-Valued Hidden Markov Models with Prior Knowledge

Chapter 57. Time Series Modeling Based on Fuzzy Transform

Chapter 58. Back to ``Reasoning''

Chapter 59. Lexicographic Choice Functions Without Archimedeanicity

Chapter 60. Composition Operator for Credal Sets Reconsidered

Chapter 61. A Nonparametric Linearity Test for a Multiple Regression Model with Fuzzy Data

Chapter 62. Treat a Weak Dependence Among Causes and Lives in Insurance by Means of Fuzzy Sets

Chapter 63. A Portfolio Diversification Strategy via Tail Dependence Clustering

Chapter 64. An Upper Bound Estimation About the Sample Average of Interval-Valued Random Sets

Chapter 65. On Asymptotic Properties of the Multiple Fuzzy Least Squares Estimator

## Book Details

- Title: Soft Methods for Data Science
- Length: 535 pages
- Edition: 1st ed. 2017
- Language: English
- Publisher: Springer
- Publication Date: 2016-08-30
- ISBN-10: 331942971X
- ISBN-13: 9783319429717

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