International Conference on Trends and Perspectives in Linear Statistical Inference, LinStat 2026

The purpose of the meeting is to bring together researchers sharing an interest in a variety of aspects of statistics and its applications as well as matrix analysis and its applications to statistics, and offer them a possibility to discuss current developments in these subjects. The conference will mainly focus on research of linear modelling methods, estimation, testing, and predictions in economic, medical, and social science data, analysis of multivariate and high-dimensional data with special regard to complex data structures, robustness of relevant statistical methods, estimation of variance components appearing in linear models, generalizations to nonlinear models, design and analysis of experiments, including optimality and comparison of linear experiments, and applications of matrix methods in statistics.

Conference subject areas include a wide range of topics ranging from linear statistical models to their applications, including (but not limited to):

• Methodology for high-dimensional data
• Algebraic methods in multivariate analysis
• Estimation, prediction and testing
• Robustness of relevant statistical methods
• Statistical inference in mixed linear models
• Design and analysis of experiments, including optimality and comparison of linear experiments
• Applications of matrix methods in statistics
• Small area estimation models
• Ordered statistics
• Statistics in applications
• Model selection methods
• Matrix-variate distributions
• Copulas
• Projection Pursuit
• New Trends in Robust Statistical Analysis theory and application
• Modeling of Covariance Structure for Continuous and Discrete Dependent Data
• Inference for Non Gaussian Distributions in Linear Models
• Design and Analysis of Experiments
• Machine Learning and Statistical Inference