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PROBASTAT 2024 — 8th International Conference on Probability and Statistics
20 mai 2024 - 24 mai 2024 • Smolenice, Slovaquie
Institute of Measurement Science of the Slovak Academy of Sciences
PROBASTAT 2024, the 8th International Conference on Probability and Statistics, celebrates a 50-year legacy of advancing the exchange of ideas and research within the statistics community. This year's conference offers a rich and engaging program, featuring both invited and contributed talks, alongside poster presentations that cover both traditional and modern aspects of statistical theory and its applications. Key research areas at PROBASTAT include, but are not limited to, statistical inference in parametric and nonparametric models, multivariate analysis, regression and mixed models, optimal experimental design, and applied statistics. The event will also feature prominent keynote lectures and specially organized sessions led by renowned experts in their fields. Additionally, select papers from PROBASTAT 2024 will be featured in a special issue of the journal Statistical Papers, published by Springer. We are looking forward to the meeting at the PROBASTAT 2024 conference.
PROBASTAT 2024 Secretariat;     Email.:
Statistical Inference in Parametric and Nonparametric Models, Multivariate Analysis, Regression and Mixed Models, Optimal Experimental Design, Applied Statistics
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Sujets apparentés:
LinStat 2024 — International Conference on Trends and Perspectives in Linear Statistical Inference
02 sep 2024 - 06 sep 2024 • Poprad, Slovaquie
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 a number of topics. The topics that have been selected so far include estimation, prediction and testing in linear models, 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.
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Dernière mise à jour: 19 avril 2024