Robustly fitting Gaussian graphical models: the R-package robFitConGraph

04/08/2022
by   Daniel Vogel, et al.
0

The paper gives a tutorial-style introduction to the R-package robFitConGraph, which provides a robust goodness-of-fit test for Gaussian graphical models.

READ FULL TEXT
research
09/22/2015

Efficient Neighborhood Selection for Gaussian Graphical Models

This paper addresses the problem of neighborhood selection for Gaussian ...
research
12/20/2021

Fast iterative proportional scaling for Gaussian graphical models

In Gaussian graphical models, the likelihood equations must typically be...
research
01/16/2013

YGGDRASIL - A Statistical Package for Learning Split Models

There are two main objectives of this paper. The first is to present a s...
research
03/29/2023

Module-based regularization improves Gaussian graphical models when observing noisy data

Researchers often represent relations in multi-variate correlational dat...
research
04/29/2020

Autoregressive Identification of Kronecker Graphical Models

We address the problem to estimate a Kronecker graphical model correspon...
research
01/18/2018

rcss: Subgradient and duality approach for dynamic programming

This short paper gives an introduction to the rcss package. The R packag...
research
10/02/2017

Detecting Epistatic Selection with Partially Observed Genotype Data Using Copula Graphical Models

Recombinant Inbred Lines derived from divergent parental lines can displ...

Please sign up or login with your details

Forgot password? Click here to reset