共查询到20条相似文献，搜索用时 401 毫秒
1.
W. E. Bardsley 《Mathematical Geology》1988,20(5):513-528
Engineering and scientific approaches to design magnitude estimation are briefly revisited. Some defense is offered for use of annual maxima in design as if they were variables from a common distribution. However, to assume any particular form of distribution tail beyond the largest data value is not justifiable, regardless of the degree of data support over the main body of the distribution. An alternative approach to the design problem is suggested through use of parameter-free nonparametric estimation using the kernel method. Some simulation results are presented which suggest that the parameter-free approach is worthy of further development. A particular advantage of nonparametric methods is that competing estimators can be checked against parametric distributions, leading to a progressive improvement in estimator accuracy.This paper was presented (by title) at Engineering Concepts, MGUS-87 Conference, Redwood City, California, 13–15 April 1987. 相似文献
2.
《地学前缘(英文版)》2016,7(1)
Learning incorporates a broad range of complex procedures. Machine learning(ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficultto-program applications, and software applications. It is a collection of a variety of algorithms(e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore,nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems. 相似文献
3.
Dealing with Zeros and Missing Values in Compositional Data Sets Using Nonparametric Imputation 总被引：5，自引：0，他引：5
The statistical analysis of compositional data based on logratios of parts is not suitable when zeros are present in a data set. Nevertheless, if there is interest in using this modeling approach, several strategies have been published in the specialized literature which can be used. In particular, substitution or imputation strategies are available for rounded zeros. In this paper, existing nonparametric imputation methods—both for the additive and the multiplicative approach—are revised and essential properties of the last method are given. For missing values a generalization of the multiplicative approach is proposed. 相似文献
4.
Structural analysis of data displaying trends may be performed with the help of generalized increments, the variance of these
increments being a function of a generalized covariance. Generalized covariances are estimated primarily by parametric methods
(i. e., methods searching for the best coefficients of a predetermined function), but also may be computed by one known nonparametric
alternative. In this paper, a new nonparametric method is proposed. It is founded on the following principles: (1) least-squares
residues are generalized increments; and (2) the generalized covariance is not a unique function, but a family of functions
(the system is indeterminate). The method is presented in a general context of a k order trend in Rd, although the full solution is given only fork = I in Ri. In Ri, higher order trends may be developed easily with the equations included in this paper. For higher dimensions in space, the
problem is more complex, but a research approach is proposed. The method is tested on soil pH data and compared to a parametric
and nonparametric method. 相似文献
5.
Spatial characterization of non-Gaussian attributes in earth sciences and engineering commonly requires the estimation of their conditional distribution. The indicator and probability kriging approaches of current nonparametric geostatistics provide approximations for estimating conditional distributions. They do not, however, provide results similar to those in the cumbersome implementation of simultaneous cokriging of indicators. This paper presents a new formulation termed successive cokriging of indicators that avoids the classic simultaneous solution and related computational problems, while obtaining equivalent results to the impractical simultaneous solution of cokriging of indicators. A successive minimization of the estimation variance of probability estimates is performed, as additional data are successively included into the estimation process. In addition, the approach leads to an efficient nonparametric simulation algorithm for non-Gaussian random functions based on residual probabilities. 相似文献
6.
Pilar García-Soidán Raquel Menezes Óscar Rubiños-López 《Environmental Earth Sciences》2012,66(2):615-624
The use of kriging for construction of prediction or risk maps requires estimating the dependence structure of the random
process, which can be addressed through the approximation of the covariance function. The nonparametric estimators used for
the latter aim are not necessarily valid to solve the kriging system, since the positive-definiteness condition of the covariance
estimator typically fails. The usage of a parametric covariance instead may be attractive at first because of its simplicity,
although it may be affected by misspecification. An alternative is suggested in this paper to obtain a valid covariance from
a nonparametric estimator through the Fourier series tool, which involves two issues: estimation of the Fourier coefficients
and selection of the truncation point to determine the number of terms in the Fourier expansion. Numerical studies for simulated
data have been conducted to illustrate the performance of this approach. In addition, an application to a real environmental
data set is included, related to the presence of nitrate in groundwater in Beja District (Portugal), so that pollution maps
of the region are generated by solving the kriging equations with the use of the Fourier series estimates of the covariance. 相似文献
7.
Noel Cressie 《Mathematical Geology》1987,19(5):425-449
Fitting trend and error covariance structure iteratively leads to bias in the estimated error variogram. Use of generalized increments overcomes this bias. Certain generalized increments yield difference equations in the variogram which permit graphical checking of the model. These equations extend to the case where errors are intrinsic random functions of order k, k=1, 2, ..., and an unbiased nonparametric graphical approach for investigating the generalized covariance function is developed. Hence, parametric models for the generalized covariance produced by BLUEPACK-3D or other methods may be assessed. Methods are illustrated on a set of coal ash data and a set of soil pH data. 相似文献
8.
This paper introduces the alternating conditional expectation (ACE) algorithm of Breiman and Friedman (J Am Stat Assoc 80:580–619,
1985) for estimating the transformations of a response and a set of predictor variables in multiple regression problems in hydrogeology.
The proposed nonparametric approach can be applied easily for estimating the optimal transformations of different hydrogeological
data to obtain maximum correlation between observed variables. The approach does not require a priori assumptions of a functional
form, and the optimal transformations are derived solely based on the data set. The advantages and applicability of this new
approach to solve different multiple regression problems in hydrogeology or in Earth Sciences are illustrated by means of
theoretical investigations and case studies. It is demonstrated that the ACE method has certain advantages in some fitting
problems of hydrogeology over the traditional multiple regression. Based on our knowledge, this is the first application of
the ACE algorithm to analyze and interpret groundwater data. 相似文献
9.
Projection Pursuit Multivariate Transform 总被引：5，自引：2，他引：3
Transforming complex multivariate geological data to a Gaussian distribution is an important and challenging problem in geostatistics. A variety of transforms are available for this goal, but struggle with high dimensional data sets. Projection pursuit density estimation (PPDE) is a well-established nonparametric method for estimating the joint density of multivariate data. A central component of the PPDE algorithm transforms the original data toward a multivariate Gaussian distribution. The PPDE approach is modified to map complex data to a multivariate Gaussian distribution within a geostatistical modeling context. Traditional modeling may then take place on the transformed Gaussian data, with a back-transform used to return simulated variables to their original units. This approach is referred to as the projection pursuit multivariate transform (PPMT). The PPMT shows the potential to be an effective means for modeling high dimensional and complex geologic data. The PPMT algorithm is developed before discussing considerations and limitations. A case study compares modeling results against more common techniques to demonstrate the value and place of the PPMT within geostatistics. 相似文献
10.
The cumulative distribution function (CDF) of magnitude of seismic events is one of the most important probabilistic characteristics in Probabilistic Seismic Hazard Analysis (PSHA). The magnitude distribution of mining induced seismicity is complex. Therefore, it is estimated using kernel nonparametric estimators. Because of its model-free character the nonparametric approach cannot, however, provide confidence interval estimates for CDF using the classical methods of mathematical statistics.To assess errors in the seismic events magnitude estimation, and thereby in the seismic hazard parameters evaluation in the nonparametric approach, we propose the use of the resampling methods. Resampling techniques applied to a one dataset provide many replicas of this sample, which preserve its probabilistic properties. In order to estimate the confidence intervals for the CDF of magnitude, we have developed an algorithm based on the bias corrected and accelerated method (BCa method). This procedure uses the smoothed bootstrap and second-order bootstrap samples. We refer to this algorithm as the iterated BCa method. The algorithm performance is illustrated through the analysis of Monte Carlo simulated seismic event catalogues and actual data from an underground copper mine in the Legnica–Głogów Copper District in Poland.The studies show that the iterated BCa technique provides satisfactory results regardless of the sample size and actual shape of the magnitude distribution. 相似文献
11.
Geologic uncertainty in a regulatory environment: An example from the potential Yucca Mountain nuclear waste repository site 总被引：1，自引：0，他引：1
Regulatory geologists are concerned with predicting the performance of sites proposed for waste disposal or for remediation of existing pollution problems. Geologic modeling of these sites requires large-scale expansion of knowledge obtained from very limited sampling. This expansion induces considerable uncertainty into the geologic models of rock properties that are required for modeling the predicted performance of the site.One method for assessing this uncertainty is through nonparametric geostatistical simulation. Simulation can produce a series of equiprobable models of a rock property of interest. Each model honors measured values at sampled locations, and each can be constructed to emulate both the univariate histogram and the spatial covariance structure of the measured data. Computing a performance model for a number of geologic simulations allows evaluation of the effects of geologic uncertainty. A site may be judged acceptable if the number of failures to meet a particular performance criterion produced by these computations is sufficiently low. A site that produces too many failures may be either unacceptable or simply inadequately described.The simulation approach to addressing geologic uncertainty is being applied to the potential high-level nuclear waste repository site at Yucca Mountain, Nevada, U.S.A. Preliminary geologic models of unsaturated permeability have been created that reproduce observed statistical properties reasonably well. A spread of unsaturated groundwater travel times has been computed that reflects the variability of those geologic models. Regions within the simulated models exhibiting the greatest variability among multiple runs are candidates for obtaining the greatest reduction in uncertainty through additional site characterization. 相似文献
12.
Yalchin Efendiev Akhil Datta-Gupta Xianlin Ma Bani Mallick 《Mathematical Geosciences》2008,40(2):213-232
In this paper, the Markov Chain Monte Carlo (MCMC) approach is used for sampling of the permeability field conditioned on
the dynamic data. The novelty of the approach consists of using an approximation of the dynamic data based on streamline computations.
The simulations using the streamline approach allows us to obtain analytical approximations in the small neighborhood of the
previously computed dynamic data. Using this approximation, we employ a two-stage MCMC approach. In the first stage, the approximation
of the dynamic data is used to modify the instrumental proposal distribution. The obtained chain correctly samples from the
posterior distribution; the modified Markov chain converges to a steady state corresponding to the posterior distribution.
Moreover, this approximation increases the acceptance rate, and reduces the computational time required for MCMC sampling.
Numerical results are presented. 相似文献
13.
The indicator kriging (IK) is one of the most efficient nonparametric methods in geo-statistics. The order relation problem in the conditional cumulative distribution values obtained by IK is the most severe drawback of it. The correction of order relation deviations is an essential and important part of IK approach. A monotone regression was proposed as a new correction method which could minimize the deviation from original quintiles value, although, ensuring all order relations. 相似文献
14.
The practice of fast conditional simulations through the LU decomposition of the covariance matrix 总被引：9，自引：0，他引：9
Francois Alabert 《Mathematical Geology》1987,19(5):369-386
The LU-matrix approach to conditional simulations allows fast generation of large numbers of realizations for a given stochastic process. Simplicity, flexibility, and quality are its main advantages. Its implementation for cases where dense grids and/or large numbers of conditioning data cause computational problems is discussed. A case study is presented. 相似文献
15.
Iason Papaioannou Daniel Straub 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2017,11(1):116-128
ABSTRACTField data is commonly used to determine soil parameters for geotechnical analysis. Bayesian analysis allows combining field data with other information on soil parameters in a consistent manner. We show that the spatial variability of the soil properties and the associated measurements can be captured through two different modelling approaches. In the first approach, a single random variable (RV) represents the soil property within the area of interest, while the second approach models the spatial variability explicitly with a random field (RF). We apply the Bayesian concept exemplarily to the reliability assessment of a shallow foundation in a silty soil with spatially variable data. We show that the simpler RV approach is applicable in cases where the measurements do not influence the correlation structure of the soil property at the vicinity of the foundation. In other cases, it is expected to underestimate the reliability, and a RF model is required to obtain accurate results. 相似文献
16.
Application of a syntactic pattern recognition technique, seismic skeletonization, to deep crustal seismic reflection data allows attributes such as energies, lengths and dips to be associated with individual reflection events. Some of these attributes exhibit fractal properties, e.g. the relationship between seismic event lengths and their spatial distribution throughout the crust. This approach provides a new technique to analyse complex geometry on seismic reflection data.Dedicated to Professor William George Laidlaw on his SIXTIETH birthday 相似文献
17.
Before optimal linear prediction can be performed on spatial data sets, the variogram is usually estimated at various lags and a parametric model is fitted to those estimates. Apart from possible a priori knowledge about the process and the user's subjectivity, there is no standard methodology for choosing among valid variogram models like the spherical or the exponential ones. This paper discusses the nonparametric estimation of the variogram and its derivative, based on the spectral representation of positive definite functions. The use of the estimated derivative to help choose among valid parametric variogram models is presented. Once a model is selected, its parameters can be estimated—for example, by generalized least squares. A small simulation study is performed that demonstrates the usefulness of estimating the derivative to help model selection and illustrates the issue of aliasing. MATLAB software for nonparametric variogram derivative estimation is available at http://www-math.mit.edu/~gorsich/derivative.html. An application to the Walker Lake data set is also presented. 相似文献
18.
Visual data exploration for hydrological analysis 总被引：6，自引：6，他引：0
Hydrological research projects for integrated water resources management such as the IWAS initiative often accumulate large
amounts of heterogeneous data from different sources. Given the number of partners taking part in such projects, surveying
and accessing the available data sets, as well as searching for a defined subset, becomes increasingly difficult. We propose
an integrated approach for a system combining visual data management and numerical simulation which allows to survey and select
data sets based on keywords such as a region of interest or given indicators. An adequate 3D visualisation of such subsets
helps to convey information and significantly supports the assessment of relations between different types of data. Furthermore,
the interface between the visual data management system and finite element codes allows for the straightforward integration
of information into the numerical simulation process and the subsequent visualisation of simulation results in a geographical
context. We demonstrate typical workflows for integration and processing within the system based on data from the IWAS model
region in Saudi Arabia and the TERENO Bode Observatory in the Harz Mountains in Germany. In addition, we present examples
for data import and export based on established standard file formats. 相似文献
19.
Peter I. Brooker 《Mathematical Geology》1985,17(1):81-90
Journel (1974) developed the turning-bands method which allows a three-dimensional data set with specified covariance to be obtained by the simulation of several one-dimensional realizations which have an intermediate covariance. The relationship between the threedimensional and one-dimensional covariance is straightforward and allows the one-dimensional covariance to be obtained immediately. In theory a dense uniform distribution of lines in three-dimensional space is required along which the one-dimensional realizations are generated; in practice most workers have been content to use the fifteen axes of the regular icosahedron. Many mining problems may be treated in two dimensions, and in this paper a turning-bands approach is developed to generate two-dimensional data sets with a specified covariance. By working in two dimensions, the area on which the data is simulated may be divided as finely as desired by the lines on which the one-dimensional realizations are first generated. The relationship between the two-dimensional and one-dimensional covariance is derived as a nontrivial integral equation. This is solved analytically for the onedimensional covariance. The method is applied to the generation of a two-dimensional data set with spherical covariance. 相似文献
20.
Estimating Pearson's Correlation Coefficient with Bootstrap Confidence Interval from Serially Dependent Time Series 总被引：7，自引：0，他引：7
Manfred Mudelsee 《Mathematical Geology》2003,35(6):651-665
Pearson's correlation coefficient, rxy, is often used when measuring the influence of one time-dependent variable on another in bivariate climate time series. Thereby, positive serial dependence (persistence) and unknown data distributions impose a challenge for obtaining accurate confidence intervals for rxy. This is met by the presented approach, employing the nonparametric stationary bootstrap with an average block length proportional to the maximum estimated persistence time of the data. A Monte Carlo experiment reveals that this method can produce accurate (in terms of coverage) confidence intervals (of type bias-corrected and accelerated). However, since persistence reduces the number of independent observations, substantially more data points are required for achieving an accuracy comparable to a situation without persistence. The experiment further shows that neglecting serial dependence may lead to serious coverage errors. The presented method proves robust with respect to distributional shape (lognormal/normal) and time spacing (uneven/even). The method is used to confirm that a previous finding of a correlation between solar activity and Indian Ocean monsoon strength in early Holocene is valid. A further result is that the correlation between sunspot number and cosmogenic 10Be concentration vanishes after approximately 1870. 相似文献