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41.
A generalized conditional intensity measure (GCIM) approach is proposed for use in the holistic selection of ground motions for any form of seismic response analysis. The essence of the method is the construction of the multivariate distribution of any set of ground‐motion intensity measures conditioned on the occurrence of a specific ground‐motion intensity measure (commonly obtained from probabilistic seismic hazard analysis). The approach therefore allows any number of ground‐motion intensity measures identified as important in a particular seismic response problem to be considered. A holistic method of ground‐motion selection is also proposed based on the statistical comparison, for each intensity measure, of the empirical distribution of the ground‐motion suite with the ‘target’ GCIM distribution. A simple procedure to estimate the magnitude of potential bias in the results of seismic response analyses when the ground‐motion suite does not conform to the GCIM distribution is also demonstrated. The combination of these three features of the approach make it entirely holistic in that: any level of complexity in ground‐motion selection for any seismic response analysis can be exercised; users explicitly understand the simplifications made in the selected suite of ground motions; and an approximate estimate of any bias associated with such simplifications is obtained. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   
42.
A new threshold method is explained in a manner suitable for workers in the general scientific area. Its application to the prediction of extreme pollutant concentrations is described and the results are compared with those of a conventional procedure, using a set of published data. A discussion concerning the difficulties of the presently used statistical technique is also included.  相似文献   
43.
In this article, we present the multivariable variogram, which is defined in a way similar to that of the traditional variogram, by the expected value of a distance, squared, in a space withp dimensions. Combined with the linear model of coregionalization, this tool provides a way for finding the elementary variograms that characterize the different spatial scales contained in a set of data withp variables. In the case in which the number of elementary components is less than or equal to the number of variables, it is possible, by means of nonlinear regression of variograms and cross-variograms, to estimate the coregionalization parameters directly in order to obtain the elementary variables themselves, either by cokriging or by direct matrix inversion. This new tool greatly simplifies the procedure proposed by Matheron (1982) and Wackernagel (1985). The search for the elementary variograms is carried out using only one variogram (multivariable), as opposed to thep(p + 1)/2 required by the Matheron approach. Direct estimation of the linear coregionalization model parameters involves the creation of semipositive definite coregionalization matrices of rank 1.  相似文献   
44.
45.
Fitting variogram models by weighted least squares   总被引:41,自引:0,他引:41  
The method of weighted least squares is shown to be an appropriate way of fitting variogram models. The weighting scheme automatically gives most weight to early lags and down-weights those lags with a small number of pairs. Although weights are derived assuming the data are Gaussian (normal), they are shown to be still appropriate in the setting where data are a (smooth) transform of the Gaussian case. The method of (iterated) generalized least squares, which takes into account correlation between variogram estimators at different lags, offer more statistical efficiency at the price of more complexity. Weighted least squares for the robust estimator, based on square root differences, is less of a compromise.  相似文献   
46.
广义岭估计的直接解法   总被引:10,自引:0,他引:10  
提出了广义岭估计的直接解法,该解法不需计算岭参数,可直接求得具有最小均方误差的解,并举例证实了该解法的优越性。  相似文献   
47.
Generalized cross-validation for covariance model selection   总被引:4,自引:0,他引:4  
A weighted cross-validation technique known in the spline literature as generalized cross-validation (GCV), is proposed for covariance model selection and parameter estimation. Weights for prediction errors are selected to give more importance to a cluster of points than isolated points. Clustered points are estimated better by their neighbors and are more sensitive to model parameters. This rational weighting scheme also provides a simplifying significantly the computation of the cross-validation mean square error of prediction. With small- to medium-size datasets, GCV is performed in a global neighborhood. Optimization of usual isotropic models requires only a small number of matrix inversions. A small dataset and a simulation are used to compare performances of GCV to ordinary cross-validation (OCV) and least-squares filling (LS).  相似文献   
48.
The Köppen climate classification was applied to the observed gridded climatological sets and the outputs of four general circulation models (GCMs) over the continents of the Earth. All data had been acquired via the Data Distribution Centre established by the Intergovernmental Panel on Climate Change. The ability of the GCMs to simulate the Köppen climate zones identified in the real data was explored and possible future (global warming) changes in the climate types' distribution for each GCM were assessed. Differences in the area distributions derived from the GCMs' recent climate simulations give evidence about uncertainties generally involved in climate models. As to the global warming simulations, all GCM projections of warming climate (horizon 2050) show that the zones representing tropical rain climates and dry climates become larger, and the zones identified with boreal forest and snow climates together with the polar climates are smaller.  相似文献   
49.
This paper analyses the topographic context of the remaining glaciated areas in the Maladeta Massif (Central Spanish Pyrenees). These ice‐covered surfaces have been incorporated into a geographic information system (GIS) in an attempt at correlating the presence of ice with a range of topographic variables obtained from a digital elevation model. The use of generalized additive models and binary regression tree models enabled us (i) to quantify the spatial variability in the distribution of glaciers attributable to characteristics of the local terrain, (ii) to investigate the interaction between the variables that account for the ice cover distribution and (iii) to map the probability of glacier development. Our results show that although the development of glaciers depends on regional climate conditions, the topographic context is of paramount importance in determining the location, extent, shape and recent evolution of each glacial body. Thus, the joint effect of altitude, exposure to incoming solar radiation, slope and mean curvature is able to explain more than 70 per cent of the observed variance. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   
50.
Modelling peak accelerations from earthquakes   总被引:1,自引:0,他引:1  
This paper deals with the prediction of peak horizontal accelerations with emphasis on seismic risk and insurance concerns. Non‐linear mixed effects models are used to analyse well‐known earthquake data and the consequences of mis‐specifying assumptions on the error term are quantified. A robust fit of the usual model, using recently developed robust weighted maximum likelihood estimators, is presented. Outlying data are automatically identified and subsequently investigated. A more appropriate model accounting for the extreme value nature of the responses, is also developed and implemented. The implication on acceleration predictions is demonstrated. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   
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