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., Claessens, S., Featherstone, W. Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum. Springer Berlin Heidelberg, 2014 с. 1081-1093,.
Filmer, M., Claessens, S., Featherstone, W. Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum. Springer Berlin Heidelberg, 2014 с. 1081-1093,.
Filmer, M., Claessens, S., Featherstone, W. (2014) Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum, Springer Berlin Heidelberg с. 1081-1093,.
Filmer, M., Claessens, S., & Featherstone, W. (2014). Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum. Springer Berlin Heidelberg, с. 1081-1093.
Filmer M, Claessens S, Featherstone W. Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum. Springer Berlin Heidelberg; 2014. p. с. 1081-1093.
