37 citations · 69 across the 12 of their papers we have counts for
14 papers
Generating large Ising models with Markov structure via simple linear relations
Nanny Wermuth, Giovanni M. Marchetti
We extend the notion of a tree graph to sequences of prime graphs which are cycles and edges and name these non-chordal graphs hollow trees. These structures are especially attract…
Pairwise Markov properties for regression graphs
Kayvan Sadeghi, Nanny Wermuth
With a sequence of regressions, one may generate joint probability distributions. One starts with a joint, marginal distribution of context variables having possibly a concentratio…
Palindromic Bernoulli distributions
Giovanni M. Marchetti, Nanny Wermuth
We introduce and study a subclass of joint Bernoulli distributions which has the palindromic property. For such distributions the vector of joint probabilities is unchanged when th…
Total positivity in Markov structures
Shaun Fallat, Steffen Lauritzen, Kayvan Sadeghi +3
We discuss properties of distributions that are multivariate totally positive of order two (MTP2) related to conditional independence. In particular, we show that any independence…
Design and interpretation of studies: relevant concepts from the past and some extensions
D. R. Cox, Nanny Wermuth
Principles for the planning and analysis of observational studies, as suggested by W.G Cochran in 1972, are discussed and compared to additional methodological developments since t…
Graphical Markov models, unifying results and their interpretation
Nanny Wermuth
Graphical Markov models combine conditional independence constraints with graphical representations of stepwise data generating processes.The models started to be formulated about…