Model-Assisted Estimation of Forest Resources With Generalized Additive Models

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Nonparametric Model Calibration Estimation in Survey Sampling (2005, methodology): “additive models proposed in literature ( Opsomer, Moisen and Kim, 2001 ) is currently being investigated by”
Model-Assisted Survey Regression Estimation with the Lasso (2017, methodology): “To obtain weights, we employ the model calibration method of Wu and Sitter (2001), used in related contexts by Montanari and Ranalli (2005b) and Opsomer et al. (2007).”
Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories (2009, methodology): “…have been exploited successfully by probability-based forest inventories in efforts to improve precision of regional or national estimates of forest resource attributes (Corona et al., 2002;Holmstromet al., 2002; Lefskyet al., 2005;McRoberts et al., 2005; Meng et al., 2007; Opsomer et al., 2007).”
Calibrated Bayes, an alternative inferential paradigm for official statistics (2012, methodology): “Opsomer et al. (2007) applied the model-assisted approach to incorporating auxiliary information into an equal probability sample, where the regression models for prediction did not include the constant term.”
Integration of forest mapping and inventory to support forest management (2010, methodology): “Examples of application of the GREG approach are provided by Moisen & Edwards (1999), Puhr & Donoghue (2000) and Opsomer et al. (2007).”