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svyratio_huber() and svyratio_tukey()); these
functions are robust alternatives to
survey::svyratio().svymean_ratio() and svytotal_ratio().MU284pps: A pps sample without replacement
of size 50 from the MU284 population in Särndal et al. (1992).Functions svymean_reg() and
svytotal_reg() are not flagged as “experimental” anymore.
Several changes took place (in fact, the functions have undergone a
complete code refactoring):
auxiliary has been replaced by the two
arguments N (population size) and totals
(i.e., population totals of non-constant explanatory variables).
Important: svymean_reg() is now called
with totals not the population means.na.rm and verbose have been
dropped (not needed).svymean_reg() and
svytotal_reg() are now implemented as g-weighted
residual variance estimators.Added documentation for variable strat in the
workplace data and updated description of variable
payroll.
Added 45-degree line in the diagnostic plot method
for “3 Response vs. Fitted values” (which = 3) of class
svyreg_rob.
Method SE() for class svyreg_rob is now
exported to the namespace.
estimator$string in the return value of function
mer() indicates the name of the underlying estimator
correctly.which = 4 in
plot) for class svyreg_rob.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 detailsinit determines the left side of the search interval
and the initial value in the minimization approachFunction 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:
svyreg_huberM() and svyreg_tukeyM(); the old
functions svyreg_huber() and svyreg_tukey()
are deprecated but are kept for compatibility reasons.inst/doc and test cases
in tests have been updatedk_Inf
is now 1e06 not 1e05; see function
svyreg_control()).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
Added DOI to all references (where available).
svyreg_huberGM()svyreg_tukey() and svyreg_tukeyGM()k winsorized mean and total; see
weighted_mean_k_winsorized() and
svymean_k_winsorized()weighted_mean_dalen() and svymean_dalen()huber2()counties, flour,
losdata, and MU284stratThe 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.
Argument type = "rwm" of
weighted_mean_huber() is not used anymore (deprecated);
instead, the type is now called "rhj".