The nonparanormal model assumes that variables follow a multivariate normal distribution after a set of unknown monotone increasing transformations. It is a flexible generalization of the normal model but retains the nice interpretability of the latter. In this paper we propose a rank-based tapering estimator for estimating the correlation matrix in the nonparanormal model in which the variable...

Vertical conduit tapering is proposed as an effective mechanism to almost eliminate the increase in hydraulic resistance with increased height. Despite this potential role, very little is known about its changes during ontogeny. Here, conduit tapering and stem morphology of young/small and old/tall individuals of Acer pseudoplatanus in the field, as well as 3-yr-old grafted trees from both age ...

The optimum wire shape for minimum signal propagation delay across an line is shown to have a general exponential form. The line inductance makes exponential tapering more attractive for lines than for lines. For lines, optimum wire tapering achieves a higher reduction in the signal propagation delay as compared to uniform wire sizing. Wire tapering can reduce both the propagation delay and pow...

We present a new method to determine contraction kernels for the construction of graph pyramids. The new method works with undirected graphs and yields a reduction factor of at least 2.0. This means that with our method the number of vertices in the subgraph induced by any set of contractible edges is reduced to half or less by a single parallel contraction. Our method yields better reduction f...

In the analysis of spatial data, the inverse of the covariance matrix needs to be calculated. For example, the inverse is needed for best linear unbiased prediction or kriging, and is repeatedly calculated in the maximum likelihood estimation or the Bayesian inferences. Since the spatial sample size can be quite large, operations on the large covariance matrix can be a numerical challenge if no...

Maximum likelihood is an attractive method of estimating covariance parameters in spatial models based on Gaussian processes. However, calculating the likelihood can be computationally infeasible for large datasets, requiring O(n3) calculations for a dataset with n observations. This article proposes the method of covariance tapering to approximate the likelihood in this setting. In this approa...

In the present work, a study of thermoelastic analysis of a rotating thick truncated conical shell subjected to the temperature gradient and non-uniform internal pressure is carried out. The formulation is based on first-order shear deformation theory (FSDT), which accounts for the transverse shear. The governing equations, derived using minimum total potential energy principle, are solved, usi...