The course covers the probability, distribution theory and statistical inference needed for advanced courses in statistics and econometrics. Michaelmas term: Probability. Conditional probability and ...

The course covers the probability and distribution theory needed for advanced courses in statistics and econometrics.: Topics covered: Probability. Conditional probability and independence. Random ...

This hinges on finding a PDE for the joint distribution of the Dyson process, which itself is based on the joint probability of the eigenvalues for coupled Gaussian Hermitian matrices. The PDE for the ...

In a random graph, counts for the number of vertices with given degrees will typically be dependent. We show via a multivariate normal and a Poisson process approximation that, for graphs which have ...