Ecologists are increasingly familiar with Bayesian statistical modeling and its associated Markov chain Monte Carlo (MCMC) methodology to infer about or to discover interesting effects in data. The ...

On Friday the 11th of November 2022, PhD, M.Sc. Laura Uusitalo defends her PhD thesis on Bayesian network modelling of complex systems with sparse data: Ecological case studies. The thesis is related ...

Functional analysis of variance (ANOVA) modeling has been proved particularly useful to investigate the dynamic changes of functional data according to certain categorical factors and their ...

We describe a Bayesian Mixture Model (BMM) incorporating a variable-selection prior and compared its performance with logistic multiple regression model (LM) in simulated case–control data with ...

Offered through an interdisciplinary partnership, data science at CU Boulder is delivered by the Departments of Applied Mathematics, Computer Science, and Information Science and awarded by the ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Description This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic ...

Kipi.ai is excited to offer its Marketing Mix Modeling and Analytics App on the Snowflake AI Data Cloud. As a trusted services partner in Snowflake’s ...