[R-sig-eco] Online course - Generalized Additive Models (GAMs) in R
Dear all, there are only 3 seats remaining for our course on Generalized Additive Models (GAMs) in R, scheduled for April 22nd-26th. Course website: https://www.physalia-courses.org/courses-workshops/gams-in-r-2/ Who Should Attend: This course is tailored for graduate students and researchers with some statistical background. If you're familiar with generalized linear models, likelihood, and AIC, this course is perfect for you. Don't worry if you're a bit rusty on these concepts – we'll provide a quick recap. Basic familiarity with RStudio and R programming is essential. By the end of this course, you will: - Gain practical insights into using GAMs to uncover relationships in data. - Learn to fit GAMs in R using the mgcv and brms packages. - Understand different types of splines and how to choose the best one for your analysis. - Master visualization techniques to interpret and validate GAMs. For the complete list of our courses and workshops, visit: https://www.physalia-courses.org/courses-workshops/ Secure your spot now and take your statistical skills to the next level! Best regards, Carlo Pecoraro, Ph.D Physalia-courses DIRECTOR i...@physalia-courses.org [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
[R-sig-eco] Online course: Generalized Additive Models (GAMs) in R
Dear all, registrations are now open for our course on Generalized Additive Models (GAMs) in R in April (22nd-26th). Course website: [ https://www.physalia-courses.org/courses-workshops/gams-in-r-2/ ]( https://www.physalia-courses.org/courses-workshops/gams-in-r-2/ ) Who is this for? Designed for graduate students and researchers with some statistical knowledge, this course caters to those familiar with generalized linear models, likelihood, and AIC. If you're a bit rusty on these concepts, worry not – we'll provide a quick recap. Familiarity with RStudio and basic R programming skills are essential. Learning Outcomes: - Understand practical aspects of GAMs for learning relationships from data. - Fit GAMs in R using the mgcv and brms packages. - Differentiate between types of splines and determine their optimal use. - Visualize fitted GAMs and validate model assumptions. For the full list of our courses and workshops, please visit: [ https://www.physalia-courses.org/courses-workshops/ ]( https://www.physalia-courses.org/courses-workshops/gams-in-r-2/ ) Best regards, Carlo Carlo Pecoraro, Ph.D Physalia-courses DIRECTOR i...@physalia-courses.org mobile: +49 17645230846 [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
