Curso online en directo: Introducción a la inferencia bayesiana, del 4 al 8 de marzo, 2024
Estimad@s colegas,
El siguiente curso puede ser de interés para miembros de esta lista: “Introduction to Bayesian Inference in Practice” – 8 edition. Este curso se realizará online en directo de manera síncrona. Máximo 18 participantes.
- Fechas y horario: del 4 al 8 de marzo, 2024, de 13:00 a 17:00 (zona horaria de Madrid).
- Profesorado: Dr. Daniele Silvestro (University of Gothenburg, Suecia) y Tobias Andermann (University of Gothenburg, Suecia)
- Resumen del curso (en inglés, que es el idioma en el que se impartirá el curso):
This course is based on the assumption that the easiest way to understand the principles of Bayesian inference and the functioning of the main algorithms is to implement these methods yourself.
The instructors will outline the relevant concepts and basic theory, but the focus of the course will be to learn how to do Bayesian inference in practice. He will show how to implement the most common algorithms to estimate parameters based on posterior probabilities, such as Markov Chain Monte Carlo samplers, and how to build hierarchical models.
He will also touch upon hypothesis testing using Bayes factors and Bayesian variable selection.
The course will take a learn-by-doing approach, in which participants will implement their own MCMCs using R or Python (templates for both languages will be provided).
After completion of the course, the participants will have gained a better understanding of how the main Bayesian methods are implemented in many programs used in biological research work. Participants will also learn how to model at least basic problems using Bayesian statistics and how to implement the necessary algorithms to solve them.
Participants are expected to have some knowledge of R or Python (each can choose their preferred language), but they will be guided “line-by-line” in writing their script. The aim is that, by the end of the week, each participant will have written their own MCMC – from scratch! Participants are encouraged to bring their own datasets and questions and we will (try to) figure them out during the course and implement scripts to analyze them in a Bayesian framework.
Más información e inscripciones https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/ o escribiendo a courses@transmittingscience.com
Un cordial saludo
Sole
Información del evento
Organizador
Transmitting Science
Correo electrónico
communication@transmittingscience.comWeb
http://www.transmittingscience.comEstimad@s colegas,
El siguiente curso puede ser de interés para miembros de esta lista: “Introduction to Bayesian Inference in Practice” – 8 edition. Este curso se realizará online en directo de manera síncrona. Máximo 18 participantes.
- Fechas y horario: del 4 al 8 de marzo, 2024, de 13:00 a 17:00 (zona horaria de Madrid).
- Profesorado: Dr. Daniele Silvestro (University of Gothenburg, Suecia) y Tobias Andermann (University of Gothenburg, Suecia)
- Resumen del curso (en inglés, que es el idioma en el que se impartirá el curso):
This course is based on the assumption that the easiest way to understand the principles of Bayesian inference and the functioning of the main algorithms is to implement these methods yourself.
The instructors will outline the relevant concepts and basic theory, but the focus of the course will be to learn how to do Bayesian inference in practice. He will show how to implement the most common algorithms to estimate parameters based on posterior probabilities, such as Markov Chain Monte Carlo samplers, and how to build hierarchical models.
He will also touch upon hypothesis testing using Bayes factors and Bayesian variable selection.
The course will take a learn-by-doing approach, in which participants will implement their own MCMCs using R or Python (templates for both languages will be provided).
After completion of the course, the participants will have gained a better understanding of how the main Bayesian methods are implemented in many programs used in biological research work. Participants will also learn how to model at least basic problems using Bayesian statistics and how to implement the necessary algorithms to solve them.
Participants are expected to have some knowledge of R or Python (each can choose their preferred language), but they will be guided “line-by-line” in writing their script. The aim is that, by the end of the week, each participant will have written their own MCMC – from scratch! Participants are encouraged to bring their own datasets and questions and we will (try to) figure them out during the course and implement scripts to analyze them in a Bayesian framework.
Más información e inscripciones https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/ o escribiendo a courses@transmittingscience.com
Un cordial saludo
Sole