c(
person("Beat", "Hulliger", email = "beat.hulliger@fhnw.ch", role = "aut"),
person("Tobias", "Schoch", email = "tobias.schoch@gmail.com", role = "aut"),
person("Martin", "Sterchi", email = "martin.sterchi@fhnw.ch", role = "cre"))
Multiple functions to compute robust survey statistics. The package
supports the computations of robust means, totals, and ratios. Available
methods are Huber M-estimators, trimming, and winsorization. The package
'robsurvey' complements the 'survey' package. The package additionally
includes a weighted version of the resistant line function of base R (line()),
as well as two median based simple regression estimators. The methods are
described in Hulliger (1995)
<https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X199500114407/>.
survey (>= 3.35-1), stats, graphics, utils
Beat Hulliger [aut],
Tobias Schoch [aut],
Martin Sterchi [cre]

c(person(
given = "Beat",
family = "Hulliger",
email = "beat.hulliger@fhnw.ch",
role = "aut"),
person(
given ="Tobias",
family = "Schoch",
email = "tobias.schoch@fhnw.ch",
role = c("aut","cre")),
person(
given = "Martin",
family = "Sterchi",
email = "martin.sterchi@fhnw.ch",
role = c("ctr", "com")))
Functions to compute robust (outlier-resistant) estimates of finite
population characteristics. The package supports the computations of robust
means, totals, ratios, etc. Available methods are regression M- and
GM-estimators, trimming, and winsorization. The package robsurvey
complements the survey.
grDevices, stats, survey (>= 3.35-1), KernSmooth
Beat Hulliger [aut],
Tobias Schoch [aut, cre],
Martin Sterchi [ctr, com]

c(person(
given = "Beat",
family = "Hulliger",
email = "beat.hulliger@fhnw.ch",
role = "aut"),
person(
given ="Tobias",
family = "Schoch",
email = "tobias.schoch@fhnw.ch",
comment = c(ORCID = "0000-0002-1640-3395"),
role = c("aut","cre")),
person(
given = "Martin",
family = "Sterchi",
email = "martin.sterchi@fhnw.ch",
role = c("ctr", "com")))
Robust (outlier-resistant) estimators of finite population
characteristics like of means, totals, ratios, regression, etc. Available
methods are M- and GM-estimators of regression, weight reduction,
trimming, and winsorization. The package extends the 'survey'
<https://CRAN.R-project.org/package=survey> package.
Beat Hulliger [aut],
Tobias Schoch [aut, cre] (<https://orcid.org/0000-0002-1640-3395>),
Martin Sterchi [ctr, com]