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 Author:
 Emery, Xavier, et al. ; Madani, Nasser; Show all 2 Author
 Source:
 Stochastic environmental research and risk assessment 2019 v.33 no.1 pp. 183199
 ISSN:
 14363240
 Subject:
 equations; models; prediction; variance
 Abstract:
 ... Cokriging allows predicting coregionalized variables from sampling information, by considering their spatial joint dependence structure. When secondary covariates are available exhaustively, solving the cokriging equations may become prohibitive, which motivates the use of a moving search neighborhood to select a subset of data, based on their closeness to the target location and the screen effect ...
 DOI:
 10.1007/s0047701815781

http://dx.doi.org/10.1007/s0047701815781
 Author:
 Emery, Xavier, et al. ; Arroyo, Daisy; Show all 2 Author
 Source:
 Stochastic environmental research and risk assessment 2018 v.32 no.11 pp. 32453255
 ISSN:
 14363240
 Subject:
 algorithms; covariance; environmental science; geometry; models
 Abstract:
 ... Intrinsic random fields of order k, defined as random fields whose highorder increments (generalized increments of order k) are secondorder stationary, are used in spatial statistics to model regionalized variables exhibiting spatial trends, a feature that is common in earth and environmental sciences applications. A continuous spectral algorithm is proposed to simulate such random fields in a d ...
 DOI:
 10.1007/s0047701815162

http://dx.doi.org/10.1007/s0047701815162
 Author:
 Emery, Xavier, et al. ; Arroyo, Daisy; Show all 2 Author
 Source:
 Stochastic environmental research and risk assessment 2018 v.32 no.4 pp. 905919
 ISSN:
 14363240
 Subject:
 algorithms; covariance; models
 Abstract:
 ... This paper presents an algorithm for simulating Gaussian random fields with zero mean and nonstationary covariance functions. The simulated field is obtained as a weighted sum of cosine waves with random frequencies and random phases, with weights that depend on the locationspecific spectral density associated with the target nonstationary covariance. The applicability and accuracy of the algor ...
 DOI:
 10.1007/s0047701714023

https://dx.doi.org/10.1007/s0047701714023
 Author:
 Emery, Xavier, et al. ; Peron, Ana; Porcu, Emilio; Show all 3 Authors
 Source:
 Stochastic environmental research and risk assessment 2018 v.32 no.11 pp. 30533066
 ISSN:
 14363240
 Subject:
 covariance; geostatistics; models
 Abstract:
 ... Nested covariance models, defined as linear combinations of basic covariance functions, are very popular in many branches of applied statistics, and in particular in geostatistics. A notorious limit of nested models is that the constants in the linear combination are bound to be nonnegative in order to preserve positive definiteness (admissibility). This paper studies nested models on ddimensiona ...
 DOI:
 10.1007/s0047701815763

http://dx.doi.org/10.1007/s0047701815763
 Author:
 Emery, Xavier, et al. ; Maleki, Mohammad; Show all 2 Author
 Source:
 Computers and Geosciences 2017 v.109 pp. 258267
 ISSN:
 00983004
 Subject:
 algorithms; copper; covariance; least squares; mineral resources; models; uncertainty
 Abstract:
 ... In mineral resources evaluation, the joint simulation of a quantitative variable, such as a metal grade, and a categorical variable, such as a rock type, is challenging when one wants to reproduce spatial trends of the rock type domains, a feature that makes a stationarity assumption questionable. To address this problem, this work presents methodological and practical proposals for jointly simula ...
 DOI:
 10.1016/j.cageo.2017.08.015

http://dx.doi.org/10.1016/j.cageo.2017.08.015
 Author:
 Emery, Xavier, et al. ; Arroyo, Daisy; Show all 2 Author
 Source:
 Stochastic environmental research and risk assessment 2017 v.31 no.7 pp. 15831592
 ISSN:
 14363240
 Subject:
 algorithms; geometry; models
 Abstract:
 ... This paper addresses the problem of simulating multivariate random fields with stationary Gaussian increments in a ddimensional Euclidean space. To this end, one considers a spectral turningbands algorithm, in which the simulated field is a mixture of basic random fields made of weighted cosine waves associated with random frequencies and random phases. The weights depend on the spectral density ...
 DOI:
 10.1007/s0047701612257

http://dx.doi.org/10.1007/s0047701612257
 Author:
 Emery, Xavier, et al. ; Madani, Nasser; Show all 2 Author
 Source:
 Stochastic environmental research and risk assessment 2017 v.31 no.4 pp. 893913
 ISSN:
 14363240
 Subject:
 algorithms; engineering; environmental science; geologists; hydrology; mining; models; oil fields
 Abstract:
 ... The plurigaussian model is used in mining engineering, oil reservoir characterization, hydrology and environmental sciences to simulate the layout of geological domains in the subsurface, while reproducing their spatial continuity and dependence relationships. However, this model is wellestablished only in the stationary case, when the spatial distribution of the domains is homogeneous in space, ...
 DOI:
 10.1007/s0047701613659

http://dx.doi.org/10.1007/s0047701613659
 Author:
 Emery, Xavier, et al. ; Safikhani, Mohammad; Asghari, Omid; Show all 3 Authors
 Source:
 Stochastic environmental research and risk assessment 2017 v.31 no.2 pp. 523533
 ISSN:
 14363240
 Subject:
 algorithms; case studies; models; reproduction; statistics
 Abstract:
 ... Sequential Gaussian simulation is one of the most widespread algorithms for simulating regionalized variables in the earth sciences. Simplicity and flexibility of this algorithm are the most important reasons that make it popular, but its implementation is highly dependent on a screen effect approximation that allows users to use a moving neighborhood instead of a unique neighborhood. Because of t ...
 DOI:
 10.1007/s0047701612551

http://dx.doi.org/10.1007/s0047701612551
 Author:
 Emery, Xavier, et al. ; Madani, Nasser; Show all 2 Author
 Source:
 Stochastic environmental research and risk assessment 2015 v.29 no.8 pp. 21732191
 ISSN:
 14363240
 Subject:
 andesite; data collection; models; uncertainty; Andes region
 Abstract:
 ... The plurigaussian model is increasingly used for simulating geodomains and quantifying geological uncertainty in the subsurface. However, because they rely on the truncation of only two Gaussian random fields, the current implementations of this model are often restricted in the number of geodomains that can be simulated and in their contact relationships. A solution to overcome these restrictio ...
 DOI:
 10.1007/s004770140997x

https://dx.doi.org/10.1007/s004770140997x
 Author:
 Emery, Xavier, et al. ; Arroyo, Daisy; Porcu, Emilio; Show all 3 Authors
 Source:
 Stochastic environmental research and risk assessment 2016 v.30 no.7 pp. 18631873
 ISSN:
 14363240
 Subject:
 algorithms; models; stochastic processes
 Abstract:
 ... We propose a spectral turningbands approach for the simulation of secondorder stationary vector Gaussian random fields. The approach improves existing spectral methods through coupling with importance sampling techniques. A notable insight is that one can simulate any vector random field whose direct and crosscovariance functions are continuous and absolutely integrable, provided that one knows ...
 DOI:
 10.1007/s0047701511510

http://dx.doi.org/10.1007/s0047701511510
 Author:
 Emery, Xavier
 Source:
 Computers & geosciences 2012 v.38 no.1 pp. 136144
 ISSN:
 00983004
 Subject:
 computer software; computers; equations; mineral resources; prediction
 Abstract:
 ... Traditional approaches to predict a secondorder stationary vector random field include simple and ordinary cokriging, depending on whether or not the mean values of the vector components are assumed to be known. This paper explores a variant of cokriging, in which the mean values of the vector components are related by linear combinations with known coefficients. Equations for the cokriging predi ...
 DOI:
 10.1016/j.cageo.2011.06.001

http://dx.doi.org/10.1016/j.cageo.2011.06.001
 Author:
 Emery, Xavier, et al. ; Hekmatnejad, Amin; Brzovic, Andrés; Schachter, Paulina; Vallejos, Javier A.; Show all 5 Authors
 Source:
 Engineering geology 2017 v.228 pp. 97106
 ISSN:
 00137952
 Subject:
 copper; data collection; engineering; geology; geostatistics; mining; models; prediction; uncertainty; Chile
 Abstract:
 ... This work addresses the problem of predicting the discontinuity intensity P32 (discontinuity area per unit volume of rock mass) in space and of quantifying the uncertainty in the true P32 values, using information from observed discontinuities intersecting boreholes. This problem is relevant in various fields of engineering, including mining applications, hydrocarbon extraction, groundwater modeli ...
 DOI:
 10.1016/j.enggeo.2017.07.012

http://dx.doi.org/10.1016/j.enggeo.2017.07.012
 Author:
 Emery, Xavier, et al. ; Pinheiro, Marisa; Vallejos, Javier; Miranda, Tiago; Show all 4 Authors
 Source:
 Engineering geology 2016 v.205 pp. 93103
 ISSN:
 00137952
 Subject:
 case studies; deformation; engineering; geology; geostatistics; models; prediction; risk analysis; spatial variation; uncertainty
 Abstract:
 ... A better characterization of complex rock masses is essential in geotechnical engineering, as the empirical systems widely used for this purpose have significant limitations and do not provide adequate answers for risk analysis. Geostatistics offers a set of tools that allow not only predicting the rock mass properties, but also mapping their heterogeneity at different spatial scales and quantifyi ...
 DOI:
 10.1016/j.enggeo.2016.03.003

http://dx.doi.org/10.1016/j.enggeo.2016.03.003
 Author:
 Emery, Xavier, et al. ; Peláez, María; Show all 2 Author
 Source:
 Computers & geosciences 2012 v.46 pp. 149156
 ISSN:
 00983004
 Subject:
 case studies; computers; mineral resources; models; principal component analysis
 Abstract:
 ... The simulation of vector random fields whose spatial correlation structure is represented by a linear coregionalization model can be performed by decomposing the vector components into spatially orthogonal factors and by simulating each factor separately. However, when the number of basic nested structures is large, so is the number of factors, making simulation computationally demanding. This pap ...
 DOI:
 10.1016/j.cageo.2012.04.025

http://dx.doi.org/10.1016/j.cageo.2012.04.025
 Author:
 Emery, Xavier, et al. ; Ortiz, Julián M.; Show all 2 Author
 Source:
 Computers & geosciences 2012 v.42 pp. 126135
 ISSN:
 00983004
 Subject:
 autocorrelation; case studies; computer software; computers; linear models; mineral resources
 Abstract:
 ... This paper deals with the simulation of a stationary vector Gaussian random field whose spatial correlation structure is given by a linear model of coregionalization. Traditionally, simulation is performed by decomposing the vector random field into a set of independent vector random fields with coregionalization models that contain a single nested structure, and a factorization of these fields in ...
 DOI:
 10.1016/j.cageo.2011.09.007

http://dx.doi.org/10.1016/j.cageo.2011.09.007
 Author:
 Emery, Xavier
 Source:
 Stochastic environmental research and risk assessment 2007 v.21 no.4 pp. 391403
 ISSN:
 14363240
 Subject:
 data collection; models; pollution; variance
 Abstract:
 ... In the analysis of regionalized data, irregular sampling patterns are often responsible for large deviations (fluctuations) between the theoretical and sample semivariograms. This article proposes a new semivariogram estimator that is unbiased irrespective of the actual multivariate distribution of the data (provided an assumption of stationarity) and has the minimal variance under a given multi ...
 DOI:
 10.1007/s0047700600723

http://dx.doi.org/10.1007/s0047700600723
 Author:
 Emery, Xavier, et al. ; Ortiz, Julián M.; Show all 2 Author
 Source:
 Computers & geosciences 2011 v.37 no.8 pp. 10151025
 ISSN:
 00983004
 Subject:
 algorithms; case studies; computer software; computers; mathematical models; mining
 Abstract:
 ... Change of support is a common issue in the geosciences when the volumetric support of the available data is smaller than that of the blocks on which numerical modeling is required. In this paper, we present two algorithms for the direct blocksupport simulation of crosscorrelated random fields that are monotonic transforms of stationary Gaussian random fields. The first algorithm is a variation o ...
 DOI:
 10.1016/j.cageo.2010.07.012

http://dx.doi.org/10.1016/j.cageo.2010.07.012
 Author:
 Emery, Xavier, et al. ; Arroyo, Daisy; Peláez, María; Show all 3 Authors
 Source:
 Computers & geosciences 2012 v.46 pp. 138148
 ISSN:
 00983004
 Subject:
 algorithms; computers; mixing
 Abstract:
 ... This paper addresses the problem of simulating a Gaussian random vector with zero mean and given variance–covariance matrix, without conditioning constraints. Variants of the Gibbs sampler algorithm are presented, based on the proposal by Galli and Gao, which do not require inverting the variance–covariance matrix and therefore allow considerable time savings. Numerical experiments are performed t ...
 DOI:
 10.1016/j.cageo.2012.04.011

http://dx.doi.org/10.1016/j.cageo.2012.04.011
 Author:
 Emery, Xavier, et al. ; Hernández, Jaime; Show all 2 Author
 Source:
 Canadian journal of forest research 2009 v.39 no.8 pp. 14651474
 ISSN:
 00455067
 Subject:
 forest inventory; sampling; algorithms; geostatistics; simulation models; data analysis; forest stands; forest plantations; forest trees; spatial distribution; equations; spatial data; Chile
 Abstract:
 ... In forest management, it is of interest to obtain detailed inventories such that the local prediction errors on forest attributes are less than a prespecified threshold, while keeping the number of ground samples as low as possible. Given an initial sampling design, we propose an algorithm to determine the additional sample locations. The algorithm relies on two tools: geostatistical simulation, w ...
 DOI:
 10.1139/X09048

http://dx.doi.org/10.1139/X09048