Stan

Contact: https://mc-stan.org/about/team/

Stan is a state-of-the-art platform for statistical modelling and high-performance statistical computation. Thousands of users rely on Stan for statistical modelling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.

Stan is open-source applied statistics software and the tutorials link to excellent Bayesian statistics related resources.

The Stan development team and many users have contributed tutorials aimed at introducing users to various aspects of statistical modelling with Stan, both in written and visual formats.

Stan is available in R, Python, Command-line terminal, MATLAB, Julia, Stata, Mathematica, and Scala.

Stan https://dresa.org.au/content_providers/stan Stan is a state-of-the-art platform for statistical modelling and high-performance statistical computation. Thousands of users rely on Stan for statistical modelling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business. Stan is open-source applied statistics software and the tutorials link to excellent Bayesian statistics related resources. The Stan development team and many users have contributed tutorials aimed at introducing users to various aspects of statistical modelling with Stan, both in written and visual formats. Stan is available in R, Python, Command-line terminal, MATLAB, Julia, Stata, Mathematica, and Scala. /system/content_providers/images/000/000/037/original/stan_logo.png?1712114933
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Tutorials to learn how to use STAN

Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics.

Keywords: Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB

Tutorials to learn how to use STAN https://dresa.org.au/materials/tutorials-to-learn-how-to-use-stan Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics. https://mc-stan.org/about/team/ Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB
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