Variance component estimation (VCE) is used to update the stochastic model in least-squares adjustments, but the uncertainty associated with the VCE-derived weights is rarely considered. Unbalanced data is where there is an unequal number of observations in each heterogeneous data set comprising the variance component groups. As a case study using highly unbalanced data, we redefine a continent-wide vertical datum from a combined least-squares adjustment using iterative VCE and its uncertainties to update weights for each data set.
Filmer, M., Featherstone, W., Claessens, S. Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum,
Springer Berlin Heidelberg, 2014, с. 1081-1093.
Filmer, M., Featherstone, W., Claessens, S. .
Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum.
: Springer Berlin Heidelberg, 2014, с. 1081-1093.
Filmer, M., Featherstone, W., Claessens, S. (2014)
Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum,
: Springer Berlin Heidelberg, с. 1081-1093
Filmer, M.,
Featherstone, W., &
Claessens, S.
(2014).
Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum. Journal of Geodesy. Springer Berlin Heidelberg 88 (11), с. 1081-1093.
