Extensive global and small-area estimation procedures for multiphase forest inventories under the design-based Monte-Carlo approach are provided. The implementation has been published in the Journal of Statistical Software (<doi:10.18637/jss.v097.i04>) and includes estimators for simple and cluster sampling published by Daniel Mandallaz in 2007 (<doi:10.1201/9781584889779>), 2013 (<doi:10.1139/cjfr-2012-0381>, <doi:10.1139/cjfr-2013-0181>, <doi:10.1139/cjfr-2013-0449>, <doi:10.3929/ethz-a-009990020>) and 2016 (<doi:10.3929/ethz-a-010579388>). It provides point estimates, their external- and design-based variances and confidence intervals, as well as a set of functions to analyze and visualize the produced estimates. The procedures have also been optimized for the use of remote sensing data as auxiliary information, as demonstrated in 2018 by Hill et al. (<doi:10.3390/rs10071052>).
Version: 1.0.0 Imports: methods, stats, utils, plyr (≥ 1.8.6), tidyr, ggplot2 Suggests: R.rsp Published: 2021-01-08 DOI: 10.32614/CRAN.package.forestinventory Author: Andreas Hill [aut, cre], Alexander Massey [aut], Daniel Mandallaz [ctb] Maintainer: Andreas Hill <andreas.hill at wald-rlp.de> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: no Citation: forestinventory citation info Materials: README, NEWS CRAN checks: forestinventory results Documentation: Reference manual: forestinventory.html , forestinventory.pdf Vignettes: The R Package forestinventory: Design-Based Global and Small Area Estimations for Multi-Phase Forest Inventories (source)Please use the canonical form https://CRAN.R-project.org/package=forestinventory to link to this page.
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