Please read the vignette.
Or, after installation, the help page:
#> 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: