Localized/Shrinkage Kriging Predictors
نویسندگان
چکیده
منابع مشابه
Some properties of nested Kriging predictors
Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational burden when the data set is large. We focus on a class of methods aiming at decreasing this computational cost, consisting in aggregating Kriging predictors based on smaller data subsets. We prove that aggregations based...
متن کاملTruncated Gaussian Kriging as an Alternative to Indicator Kriging
Truncated Gaussian simulation (TGS) and plurigaussian simulation (PGS) are widely accepted methods for generating realisations of geological domains (lithofacies) that reproduce contact relationships. The realisations can be used to evaluate transfer functions related to the lithofacies occurrence, the simplest ones of which are the probability of occurrence of each lithofacies and the most pro...
متن کاملLimit Kriging
A new kriging predictor is proposed. It gives a better performance over the existing predictor when the constant mean assumption in the kriging model is unreasonable. Moreover, the new predictor seems to be robust to the misspecifications in the correlation parameters. The advantages of the new predictor is demonstrated using some examples from the computer experiments literature.
متن کاملKriging Allan
" Kriging " (after the South African mining engineer Danie Krige) is a term used for a family of methods for minimum error variance estimation. Consider a linear estimatê z 0 = ˆ z(r 0) at a location r 0 based on N measurements z = [z(r 1),. .. , z(r N)] T = [z 1 ,. .. , z N ] T ˆ z 0 = w 0 + N i=1 w i z i = w 0 + w T z, (1) where w i are the weights applied to z i. We consider z i as particula...
متن کاملSpatiotemporal Kriging with External Drift
In statistics it is often assumed that sample observations are independent. But sometimes in practice, observations are somehow dependent on each other. Spatiotemporal data are dependent data which their correlation is due to their spatiotemporal locations.Spatiotemporal models arise whenever data are collected across bothtime and space. Therefore such models have to be analyzed in termsof thei...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Geosciences
سال: 2015
ISSN: 1874-8961,1874-8953
DOI: 10.1007/s11004-015-9626-6