This paper addresses the issue of incorporating a digital elevation model into the mapping of Ž . annual and monthly erosivity values in the Algarve region Portugal . Besides linear regression of erosivity against elevation, three geostatistical algorithms are introduced: simple kriging with Ž . Ž . varying local means SKlm , kriging with an external drift KED and colocated cokriging. Cross val...

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill...

Abstract Human movement studies and analyses have been fundamental in many scientific domains, ranging from neuroscience to education, pattern recognition robotics, health care sports, beyond. Previous speech motor models were proposed understand how is produced the resulting varies when some parameters are changed. However, inverse approach, which muscular response subject’s age derived real c...

This paper investigates the benefits of integrating coarse resolution satellite-derived precipitation estimates with quasi-point rain gauge data for generating a fine spatial resolution precipitation map product. To integrate the two precipitation data sources, a geostatistical downscaling and integration approach is presented that can account for the differences in spatial resolution between d...

Data recovery and reconstruction methods for unsteady flow fields with spatio-temporal missing data are studied based on proper orthogonal decomposition (POD) and on Kriging interpolation. It is found that for sufficient temporal resolution, POD-based methods outperform Kriging interpolation. However, for insufficient temporal resolution, large spatial gappiness or for flow fields with black zo...

This work is devoted to the construction of new kriging-based interpolating position-dependent subdivision schemes for data reconstruction. Their originality stands in the coupling of the underlying multi-scale framework associated to subdivision schemes with kriging theory. Thanks to an efficient stencil selection, they allow to cope the problem of non-regular data prediction while keeping the...

BACKGROUND: There is considerable interest in the literature on disease mapping to interpolate estimates of disease occurrence or risk of disease from a regional database onto a continuous surface. In addition to many interpolation techniques available the geostatistical method of kriging has been used but also criticised. RESULTS: To circumvent these critics one may use kriging along with alre...

We evaluate the performance and statistical accuracy of the fast Fourier transform method for unconditional and conditional simulation. The method is applied under difficult but realistic circumstances of a large field (1001 by 1001 points) with abundant conditioning criteria and a band limited, anisotropic, fractal-based statistical characterization (the von Kármán model). The simple Fourier u...

In this work, we investigate the issue of providing a statistical model for the response of a computer model-described nuclear engineering system, for use in uncertainty propagation. The motivation behind our approach is the need for providing an uncertainty assessment even in the circumstances where only a few samples are available. Building on our recent work in using a regression approach wi...