BLUE against OLSE in the location model: energy minimization and asymptotic considerations
In: Statistical papers, Band 64, Heft 4, S. 1187-1208
ISSN: 1613-9798
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In: Statistical papers, Band 64, Heft 4, S. 1187-1208
ISSN: 1613-9798
In: Statistical papers, Band 59, Heft 4, S. 1325-1337
ISSN: 1613-9798
In: Statistical papers, Band 65, Heft 4, S. 1985-2009
ISSN: 1613-9798
AbstractWe consider the problem of predicting values of a random process or field satisfying a linear model $$y(x)=\theta ^\top f(x) + \varepsilon (x)$$
y
(
x
)
=
θ
⊤
f
(
x
)
+
ε
(
x
)
, where errors $$\varepsilon (x)$$
ε
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x
)
are correlated. This is a common problem in kriging, where the case of discrete observations is standard. By focussing on the case of continuous observations, we derive expressions for the best linear unbiased predictors and their mean squared error. Our results are also applicable in the case where the derivatives of the process y are available, and either a response or one of its derivatives need to be predicted. The theoretical results are illustrated by several examples in particular for the popular Matérn 3/2 kernel.
In: International journal of forecasting, Band 25, Heft 1, S. 103-118
ISSN: 0169-2070
In: Statistical papers, Band 60, Heft 2, S. 545-564
ISSN: 1613-9798
In: Statistical papers, Band 57, Heft 4, S. 1059-1075
ISSN: 1613-9798