Blogs differ from other media in that authors are usually not remunerated and inscribe themselves in communities of similarly minded individuals. Bloggers value reciprocal attention, interaction with other bloggers and information from reading other blogs; they value being read but also writing...

Bloggers devote significant time not only producing content for others to read, watch or listen to, but also paying attention to and engaging in interactions with other bloggers. We hope to throw light not only on the factors that gain bloggers significant readership and lively interactions with...

In this paper, we establish three identities which play a crucial role in deriving the asymptotic distributional risk function and the asymptotic distributional bias of a large class of estimators of a matrix parameter. In particular, we generalize the results in Judge and Bock (The statistical...

Multicanonical MCMC (Multicanonical Markov Chain Monte Carlo; Multicanonical Monte Carlo) is discussed as a method of rare event sampling. Starting from a review of the generic framework of importance sampling, multicanonical MCMC is introduced, followed by applications in random matrices,...

We derive strong uniform approximations for the eigenvalues in general Laguerre and Hermite beta-ensembles by showing that the maximal discrepancy between the suitably scaled eigenvalues and roots of orthogonal polynomials converges almost surely to zero when the dimension converges to infinity....

By using a symbolic method, known in the literature as the classical umbral calculus, the trace of a non-central Wishart random matrix is represented as the convolution of the traces of its central component and of a formal variable matrix. Thanks to this representation, the moments of this...

We investigate whether quantities such as the global spectral density or individual eigenvalues of financial covariance matrices can be best modelled by standard random matrix theory or rather by its generalisations displaying power-law tails. In order to generate individual eigenvalue...

Random matrix theory (RMT) has been applied to the analysis of the cross-correlation matrix of a financial time series. The most important findings of previous studies using this method are that the eigenvalue spectrum largely follows that of random matrices but the largest eigenvalue is at...