| robsurvey-package | R Documentation |
A key design pattern of the package is that the majority of the estimating methods is available in two "flavors":
bare-bone methods
survey methods
Bare-bone methods are stripped-down versions of the survey methods in terms of functionality and informativeness. These functions may serve users and package developers as building blocks. In particular, bare-bone functions cannot compute variances.
The survey methods are much more capable and depend, for variance estimation, on the survey package.
Bare-bone methods: weighted_mean_trimmed and
weighted_total_trimmed
Survey methods: svymean_trimmed and
svytotal_trimmed
Bare-bone methods:
weighted_mean_winsorized and
weighted_total_winsorized
weighted_mean_k_winsorized and
weighted_total_k_winsorized
Survey methods:
svymean_winsorized and
svytotal_winsorized
svymean_k_winsorized and
svytotal_k_winsorized
Bare-bone methods: weighted_mean_dalen and
weighted_total_dalen
Survey methods: svymean_dalen and
svytotal_dalen
Bare-bone methods:
weighted_mean_huber and
weighted_total_huber
weighted_mean_tukey and
weighted_total_tukey
huber2 (weighted Huber Proposal 2
estimator)
Survey methods:
svymean_huber and
svytotal_huber
svymean_tukey and
svytotal_tukey
mer (minimum estimated risk estimator)
svyreg
Regression M-estimators: svyreg_huberM and
svyreg_tukeyM
Regression GM-estimators (Mallows and Schweppe):
svyreg_huberGM and svyreg_tukeyGM
Ratio M-estimators:
svyratio_huber and svyratio_tukey
Note: The functions svyreg_huber and
svyreg_tukey are deprecated, use instead
svyreg_huberM and svyreg_tukeyM, respectively;
see also robsurvey-deprecated.
Regression predictors: svymean_reg and
svytotal_reg
Ratio predictors: svymean_ratio and
svytotal_ratio
weighted_quantile and weighted_median
weighted_mad and weighted_IQR
weighted_mean and weighted_total
weighted_line, weighted_median_line,
and weighted_median_ratio
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