Please read thevignette.
Or, after installation, the help page:
help("maSAE-package",package ="maSAE")#> Mandallaz' Model-Assisted Small Area Estimators#> #> Description:#> #> An S4 implementation of the unbiased extension of the#> model-assisted' synthetic-regression estimator proposed by#> Mandallaz (2013), Mandallaz et al. (2013) and Mandallaz (2014).#> It yields smaller variances than the standard bias correction, the#> generalised regression estimator.#> #> Details:#> #> This package provides Mandallaz' extended synthetic-regression#> estimator for two- and three-phase sampling designs with or#> without clustering.#> See vignette("maSAE", package = "maSAE") and demo("maSAE", package#> = "maSAE") for introductions, '"class?maSAE::saeObj"' and#> '"?maSAE::predict"' for help on the main feature.#> #> Note:#> #> Model-assisted estimators use models to improve the efficiency#> (i.e. reduce prediction error compared to design-based estimators)#> but need not assume them to be correct as in the model-based#> approach, which is advantageous in official statistics.#> #> References:#> #> Mandallaz, D. 2013 Design-based properties of some small-area#> estimators in forest inventory with two-phase sampling. Canadian#> Journal of Forest Research *43*(5), pp. 441-449. doi:#> \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("10.1139/cjfr-2012-0381")}.#> #> Mandallaz, and Breschan, J. and Hill, A. 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 estimation. Canadian#> Journal of Forest Research *43*(11), pp. 1023-1031. doi:#> \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("10.1139/cjfr-2013-0181")}.#> #> Mandallaz, D. 2014 A three-phase sampling extension of the#> generalized regression estimator with partially exhaustive#> information. Canadian Journal of Forest Research *44*(4), pp.#> 383-388. doi:#> \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("10.1139/cjfr-2013-0449")}.#> #> See Also:#> #> There are a couple packages for model-*based* small area#> estimation, see 'sae', 'rsae', hbsae and 'JoSAE'. In 2016, Andreas#> Hill published 'forestinventory', another implementation of#> Mandallaz' model-assisted small area estimators (see#> 'vignette("forestinventory_and_maASE", package = "maSAE")' for a#> comparison).#> #> Examples:#> #> ## Not run:#> #> vignette("maSAE", package = "maSAE")#> ## End(Not run)#> #> ## Not run:#> #> demo("design", package = "maSAE")#> ## End(Not run)#> #> ## Not run:#> #> demo("maSAE", package = "maSAE")#> ## End(Not run)#>You can install maSAE from gitlab via:
if (!require("remotes"))install.packages("remotes")remotes::install_gitlab("fvafrCU/maSAE")