Results 211 to 220 of about 2,909,867 (244)

Nonparametric Regression, Kriging and Process Optimization

1995
Thin plate splines and kriging models are proposed as methods for approximating unknown response functions in the context of process optimization. Connections between the methods are discussed and implementation of the models using S-PLUS is described.
M. O’Connell, P. Haaland, S. Hardy, D. Nychka   +3 more
openaire   +1 more source

Bayesian model averaging for Kriging regression structure selection

Probabilistic Engineering Mechanics, 2019
Abstract Kriging metamodels are widely used to approximate the response of computationally-intensive engineering models for a variety of applications, ranging from system design to uncertainty quantification. Their predictions are formulated by combining a regression that captures global trends of the true model with a Gaussian process approximation ...
Zhang, Jize, Taflanidis, Alexandros A.
openaire   +2 more sources

Combining Regression Kriging With Machine Learning Mapping for Spatial Variable Estimation

IEEE Geoscience and Remote Sensing Letters, 2020
Spatial variable estimation is a basic application of geostatistics. In general, this task is performed based on observations of limited points. For some cases, intensive observed data obtained from other sources are also available as the auxiliary ...
Xiuquan Li, Y. Ao, Shuang Guo, Liping Zhu   +3 more
semanticscholar   +1 more source

[Spatial interpolation of soil organic matter using regression Kriging and geographically weighted regression Kriging].

Ying yong sheng tai xue bao = The journal of applied ecology, 2016
Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control.
Shun-hua, Yang, Hai-tao, Zhang, Long, Guo, Yan, Ren   +3 more
openaire   +1 more source

Evaluation of Groundwater Levels in the Arapahoe Aquifer Using Spatiotemporal Regression Kriging

Water Resources Research, 2019
Groundwater monitoring is fundamental to understanding system dynamics, trends in storage, and the long‐term sustainability of an aquifer. Water‐level data are the key source of information used to understand the response. However, groundwater‐level data
C. Ruybal, T. Hogue, J. McCray
semanticscholar   +1 more source

Estimating Soil Organic Matter Content by Regression Kriging

2010
In Mediterranean countries soil organic matter (SOM) depletion is a key factor in land degradation. Here, climate (temperate winter/dry summer) and water scarcity give rise to faster mineralization rates and lower accumulation intensities, particularly in association with intensive and non-conservative agronomic practices.
A. Marchetti, C. Piccini, R. Francaviglia, S. Santucci, I. Chiuchiarelli   +4 more
openaire   +1 more source

Linear Regression and Simple Kriging

1998
Linear regression is presented in the case of two variables and then extended to the multivariate case. Simple kriging is a transposition of multiple regression in a spatial context. The algebraic problems generated by missing values in the multivariate case serve as a motivation for introducing a covariance function in the spatial case.
openaire   +1 more source

Estimating Spatial Precipitation Using Regression Kriging and Artificial Neural Network Residual Kriging (RKNNRK) Hybrid Approach

Water Resources Management, 2015
A hybrid model, combining regression kriging and neural network residual kriging (RKNNRK), is developed for determining spatial precipitation distribution. The RKNNRK model is compared with current spatial interpolation models, including simple kriging (SK), ordinary kriging (OK), universal kriging (UK), regression kriging (RK) and neural network ...
Youngmin Seo, Sungwon Kim, Vijay P. Singh   +2 more
openaire   +1 more source

A comparison of kriging, co-kriging and kriging combined with regression for spatial interpolation of horizon depth with censored observations

Geoderma, 1995
Abstract We compared the performances of kriging and two methods of interpolation which allow to account for an auxiliary variable: co-kriging, and kriging combined with regression. These two methods were applied to improve the interpolation of the soft layers depth (Dsl) measured by augering, using the bulk soil electrical conductivity (ECa ...
Knotters, M., Brus, D.J., Oude Voshaar, J.H.   +2 more
openaire   +2 more sources

Downscaling MODIS images with area-to-point regression kriging

Remote Sensing of Environment, 2015
Abstract The first seven bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used widely for global land-cover/land-use (LCLU) monitoring (e.g., deforestation over the Amazon basin). However, the spatial resolution of MODIS bands 3–7 (i.e., 500 m) is coarser than that of bands 1 and 2 (i.e., 250 m), and may be too coarse
Wang, Qunming, Shi, Wenzhong, Atkinson, Peter Michael, Zhao, Yuanling   +3 more
openaire   +1 more source