1 citations · 1 across the 5 of their papers we have counts for
5 papers
Computer Algebra in R Bridges a Gap Between Mathematics and Data in the Teaching of Statistics and Data Science
Mikkel Meyer Andersen, Søren Højsgaard
The capability of R to do symbolic mathematics is enhanced by the caracas package. This package uses the Python computer algebra library SymPy as a back-end but caracas is tightly…
Unity Smoothing for Handling Inconsistent Evidence in Bayesian Networks and Unity Propagation for Faster Inference
Mads Lindskou, Torben Tvedebrink, Poul Svante Eriksen +2
We propose Unity Smoothing (US) for handling inconsistencies between a Bayesian network model and new unseen observations. We show that prediction accuracy, using the junction tree…
On some algorithms for estimation in Gaussian graphical models
Søren Højsgaard, Steffen Lauritzen
In Gaussian graphical models, the likelihood equations must typically be solved iteratively. We investigate two algorithms: A version of iterative proportional scaling which avoids…
Computer Algebra in R with caracas
Mikkel Meyer Andersen, Søren Højsgaard
The capability of R to do symbolic mathematics is enhanced by the caracas package. This package uses the Python computer algebra library SymPy as a back-end but caracas is tightly…
sparta: Sparse Tables and their Algebra with a View Towards High Dimensional Graphical Models
Mads Lindskou, Søren Højsgaard, Poul Svante Eriksen +1
A graphical model is a multivariate (potentially very high dimensional) probabilistic model, which is formed by combining lower dimensional components. Inference (computation of co…