Sensitivity Analysis of Spatial Sampling Designs for Optimal Prediction
Authors
Abstract:
In spatial statistic, the data analyzed which is correlated and this correlation is due to their locations in the studied region. Such correlation that is related to distance between observations is called spatial correlation. Usually in spatial data analysis, the prediction of the amount of uncertain quantity in arbitrary 4locations of the area is considered according to attained observations from sampling points. Thus, supposing being certain the sample size, it is necessary to select a sampling design which its observations are attained from the best prediction in mentioned points that is called spatial sampling design for prediction. In this paper, the determination of such design is considered. For this, suppose that ... [To continue please click here]
similar resources
Determination of Optimal Sampling Design for Spatial Data Analysis
Extended Abstract. Inferences for spatial data are affected substantially by the spatial configuration of the network of sites where measurements are taken. Consider the following standard data-model framework for spatial data. Suppose a continuous, spatially-varying quantity, Z, is to be observed at a predetermined number, n, of points ....[ To Countinue Click here]
full textOptimal Network Designs for Spatial Prediction
A practical problem in spatial statistics is that of constructing spatial sampling designs for environmental monitoring networks. Among the several purposes for which a monitoring network may be designed for, there is that of interpolation. In this paper, a criterion for spatial designs that emphasize the utility of the network for spatial interpolation of a random field X is discussed. Within ...
full textCompetitive Comparison of Optimal Designs of Experiments for Sampling-based Sensitivity Analysis
Nowadays, the numerical models of real-world structures are more precise, more complex and, of course, more time-consuming. Despite the growth of a computational performance, the exploration of model behaviour remains a complex task. The sensitivity analysis is a basic tool for investigating the sensitivity of the model to its inputs. One widely used strategy to assess the sensitivity is based ...
full textReliability of sampling designs for spatial snow surveys
Spatial patterns are an inherent property of most naturally occurring materials at a large range of scales. To describe spatial patterns in the field, several observations are made according to a certain sampling design. The spatial structure can be described by the semivariogram range, and nugget and sill variances. We test how reliably seven sampling designs estimate these parameters for simu...
full textA study on sensitivity of spatial sampling designs to a priori discretization schemes
In a previous paper (Environ. Ecol. Stat. 5 (1998) 29.) we presented an entropy-based approach to spatial sampling design in a state-space model framework. We now address the problem of sensitivity of optimal designs with respect to the configuration of the set of potential observation sites considered, as well as to the model specifications. The latter involve both the spatial dependence struc...
full textMy Resources
Journal title
volume 5 issue 1
pages 1- 18
publication date 2008-09
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023