International Conference on Statistics and Analysis ICSA on November 11-12, 2026 in Tokyo, Japan

Advances in Mixture Models
Analysis of Symbolic and Structured Data
Applications in Macro-Economics, Finance and Marketing
Association Rules
Bayesian Computation methods
Biostatistics and Bio-computing
Business Intelligence
Categorical Data Analysis
Classification and Discrimination
Clinical Trials
Clustering
Computational Bayesian Methods
Computational Econometrics
Computational Methods for Industry
Computational Methods in Official Statistics
Computational Statistics in Finance
Computational Statistics Teaching
Computer-intensive methods for dependent data
Data Analysis Techniques for Evaluating Trading Strategies
Data assimilation and its application
Data Mining
Data Streams and Massive data
Design of Experiments
Dimensionality Reduction
Econometrics and Statistical Finance
Environmental Statistics and Climate Change
Financial econometrics
Flexible function estimation in high dimensional problems
Functional Data Analysis
Functional Genomics: Computational and Statistical Aspects
Fuzzy Statistical Analysis
Genomics and Microarray Data Analysis
Graphical Models and Bayes Nets Computation
Graphics and Data Visualization
Image and Signal Processing
Imprecise Data and Fuzzy Methods
Internet Based Methods
Latent Variable and Structural Equation Models
Machine Learning and Scientific Computing
Matrix Computations and Statistics
Metadata and Data Representation
Mixed models for Complex and Large Problems
Model Selection, Computational Methods, and Optimization Heuristics
Models and methods for Customer Relationship Management
Multiple Testing Procedures
Multivariate Data Analysis
Neural Networks and Genetic Algorithms
New developments in software for statistical computing
Nonlinear time series modelling
Nonparametric Statistics and Smoothing
Optimization Algorithms
Partial Least Squares: A Framework for Data Analysis and Statistical Modeling
Pattern Recognition
QR factorizations and other rank-revealing factorizations
QStatistical Learning Methods involving Dimensionality Reduction
Random Search Algorithms
Recursive Partitioning and related methods
Resampling Methods
Risk Analysis and Scoring
Robust and Nonparametric Methods
Robust data mining
Robustness
Sensometrics
Signal Extraction and Filtering
Simulation
Software Development Projects
Software Evaluation
Spatial Statistics
Statistical Algorithms and Software
Statistical Databases
Statistical Education and Web Based Teaching
Statistical Matching and Data Imputation
Statistical Methods for Marketing
Statistical Signal Extraction and Filtering
Statistics for Functional data
Structural Equations Models
Support Vector Machine