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robsurvey VERSION 0.3 (2022-06-04)

NEW FEATURES

• Diagnostic plots for fitted regression model, i.e., objects of class svyreg_rob

• Robust regression: If the estimated regression scale (by default weighted MAD) is zero (or nearly so), the weighted IQR is tried instead. If the weighted IQR ist also zero, the function returns with an error.

• Function mer() for minimum estimated risk estimation of location gained two new arguments:

  • method : the method used in the search for a minimum, e.g., "Brent", "BFGS", see stats::optim() for more details
  • init determines the left side of the search interval and the initial value in the minimization approach

• Function mse() computes/ extracts the estimated mean square error/ estimated risk in presence of representative outliers; see also mer()

• Robust generalized regression estimation (GREG) of the mean and total; see svymean_reg() and svytotal_reg(). The current implementation of the functions is EXPERIMENTAL and a warning is issued when calling the functions (unless verbose = FALSE). Experimental features may:

  • have undergone less extensive testing than is normal for standard features
  • interact with unstable (external) dependencies
  • be subject to change
  • not be directly supported by the developers in the event issues arise

CHANGES

• The default functions for regression M-estimators are now called svyreg_huberM() and svyreg_tukeyM(); the old functions svyreg_huber() and svyreg_tukey() are deprecated but are kept for compatibility reasons.
• Documentation files in folder inst/doc and test cases in tests have been updated
• Several internal changes (e.g., default value of k_Inf is now 1e06 not 1e05; see function svyreg_control()).

BUG FIX

For designs with unequal probability sampling, the variance estimates of the robust estimators of mean and total are now identical with the estimates of survey::svymean() and survey::svytotal() if the tuning constant is k = Inf or LB = 0 and UB = 1

MISC

Added DOI to all references (where available).

robsurvey VERSION 0.2 (2022-01-17)

NEW FEATURES

• Weighted regression GM-estimators; see e.g., svyreg_huberGM()
• M- and GM-estimator of regression with Tukey biweight psi-function; see svyreg_tukey() and svyreg_tukeyGM()
• Weighted k winsorized mean and total; see weighted_mean_k_winsorized() and svymean_k_winsorized()
• Dalen’s weight reduction estimator of the mean and total; see weighted_mean_dalen() and svymean_dalen()
• Weighted M-estimator of the mean and total with Tukey biweight psi-function
• Weighted Huber Proposal 2 estimator; see huber2()
• Data sets counties, flour, losdata, and MU284strat

BUG FIX

The original C implementation of wquantile was buggy (with implications for the R function weighted_quantile() and also the iterative re-weighted least squares algorithm). The new C implementation of wquantile is sound.

CHANGE

Argument type = "rwm" of weighted_mean_huber() is not used anymore (deprecated); instead, the type is now called "rhj".

CHANGE of LICENSE and MAINTAINER

• The authors agreed on November 25, 2020, to license/ re-license the package version 0.2 under the GPL-2 resp. GPL-3 license. (Version 0.1 has been licensed under the MIT license).
• Tobias Schoch is now the maintainer of the package.