The R Package forestinventory: Design-Based Global and Small Area Estimations for Multiphase Forest Inventories
Open Access
- 1 January 2021
- journal article
- research article
- Published by Foundation for Open Access Statistic in Journal of Statistical Software
- Vol. 97 (4), 1-40
- https://doi.org/10.18637/jss.v097.i04
Abstract
The R Package forestinventory: Design-Based Global and Small Area Estimations for Multiphase Forest InventoriesKeywords
This publication has 13 references indexed in Scilit:
- Design-based regression estimation of net change for forest inventoriesCanadian Journal of Forest Research, 2015
- Integrating remote sensing and past inventory data under the new annual design of the Swiss National Forest Inventory using three-phase design-based regression estimationCanadian Journal of Forest Research, 2014
- National forest inventories in the service of small area estimation of stem volumeCanadian Journal of Forest Research, 2014
- A three-phase sampling extension of the generalized regression estimator with partially exhaustive informationCanadian Journal of Forest Research, 2014
- Combining double sampling for stratification and cluster sampling to a three-level sampling design for continuous forest inventoriesEuropean Journal of Forest Research, 2013
- New regression estimators in forest inventories with two-phase sampling and partially exhaustive information: a design-based Monte Carlo approach with applications to small-area estimationCanadian Journal of Forest Research, 2013
- Design-based properties of some small-area estimators in forest inventory with two-phase samplingCanadian Journal of Forest Research, 2013
- A three-phase sampling procedure for continuous forest inventory with partial re-measurement and updating of terrestrial sample plotsEuropean Journal of Forest Research, 2012
- Small area estimation of forest attributes in the Norwegian National Forest InventoryEuropean Journal of Forest Research, 2012
- Double sampling for stratification in periodic inventories—Infinite population approachForest Ecology and Management, 2010