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On a continuous spectral algorithm for simulating non stationary Gaussian random fields
(Springer, 2018)
This paper presents an algorithm for simulating
Gaussian random fields with zero mean and non-stationary
covariance functions. The simulated field is obtained as a
weighted sum of cosine waves with random frequencies
and ...
On a continuous spectral algorithm for simulating non-stationary Gaussian random fields
(Springer New York LLC, 2018)
This paper presents an algorithm for simulating Gaussian random fields with zero mean and non-stationary covariance functions. The simulated field is obtained as a weighted sum of cosine waves with random frequencies and ...
Simulation of intrinsic random fields of order k with a continuous spectral algorithm
(Springer New York LLC, 2018)
Intrinsic random fields of order k, defined as random fields whose high-order increments (generalized increments of order
k) are second-order stationary, are used in spatial statistics to model regionalized variables ...
Simulation of Intrinsic Random Fields of Order k with Gaussian Generalized Increments by Gibbs Sampling
(Springer, 2015)
This work pertains to the simulation of an intrinsic random field of order k
with a given generalized covariance function and multivariate Gaussian generalized
increments. An iterative algorithm based on the Gibbs sampler ...
Plurigaussian modeling of geological domains based on the truncation of non-stationary Gaussian random fields
(Springer, 2017)
The plurigaussian model is used in miningengineering, oil reservoir characterization, hydrology andenvironmental sciences to simulate the layout of geologicaldomains in the subsurface, while reproducing their spatialcontinuity ...
Simulation of non-stationary non-Gaussian random fields from sparse measurements using Bayesian compressive sampling and Karhunen-Loève expansion
(Elsevier BVUniversidad EAFIT. Departamento de Ingeniería Mecánica, 2019-03-20)
The first step to simulate random fields in practice is usually to obtain or estimate random field parameters, such as mean, standard deviation, correlation function, among others. However, it is difficult to estimate these ...
Modeling and estimation of some non Gaussian random fieldsModeling and estimatión of some non gaussian random fields
(2018)
In this work, we propose two types of models for the analysis of regression and dependence of positive and continuous spatio-temporal data, and of continuous spatio-temporal data with possible asymmetry and/or heavy tails. ...
Joint simulation of stationary grade and non stationary rock type for quantifying geological uncertainty in a copper deposit
(Elsevier, 2017)
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 ...
Joint simulation of stationary grade and non-stationary rock type for quantifying geological uncertainty in a copper deposit
(Elsevier, 2017)
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 ...
Quasi-stationary distributions for structured birth and death processes with mutations
(2011)
We study the probabilistic evolution of a birth and death continuous time
measure-valued process with mutations and ecological interactions. The individuals
are characterized by (phenotypic) traits that take values in a ...