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Tutorials on "R Programming and mixture models, with application to image analysis" will take place on Friday the 13th of December 2019. The number of participants to the tutorials is limited and restricted only to those who attend the conference. For further information send an email to info@CMStatistics.org.
Participants will be expected to have their own laptop with the RStudio installed. The tutorials assumes basic working knowledge in R, but no advanced programming skills required.
A link with some material will be provided to the students in due course.
Venue: Senate House University of London.Title: Introduction to R Programming and EM algorithm for Gaussian mixtures:
Prof. Jochen Einbeck, Durham University, UK.
Email: Contact
Material
Part I: Using R Notebooks, workspace handling, vectors, matrices, and data frames, reading in data, basic programming devices such as if...then, for, while, apply, functions. Application to real data sets, including data from the energy sector.
Part II: Apply the techniques from the first part to implement your own EM algorithm for Finite Gaussian Mixtures. A brief introduction to Gaussian mixtures is also given.
Title: Clustering methods for Image Analysis
Prof. Jochen Einbeck, Durham University, UK.
Email: Contact
Material
We use clustering techniques, such as k-means, mean shift clustering, or Gaussian mixtures, for image segmentation and `cleaning' of images. Participants who have attended Part II of the course can apply their own EM algorithm for this task; otherwise existing R functions can be used.
