This paper proposes a regularisation method for the estimation of large covariance matrices that uses insights from the … of estimating the theoretical constant arising in the rate of convergence of existing thresholding estimators, and hence … it is easy to implement and does not require cross-validation. The MT estimator of the sample correlation matrix is shown …

modelling that enables stochastic structural change in model parameters and on model estimation by Bayesian or non …-parametric kernel methods. In the context of the estimation of covariance matrices of large dimensional panels, such data requires … applicable in econometric analysis beyond estimation of large covariance matrices. We discuss the utility of the robust …

Probabilistic editing has been introduced to enable valid inference using established survey sampling theory in … survey sampling, and cannot provide expressions for point and variance estimates that account for the uncertainties … probabilistic editing by proposing an estimation procedure that provides valid inference when two kinds of nonsampling error are …

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors …

fixed coefficient and the rest a time-varying one. We provide an estimation method and establish associated theoretical …