Weighted Huber and Tukey M-estimator of the mean and total
(bare-bone function with limited functionality; see
svymean_huber
, svymean_tukey
,
svytotal_huber
, and svytotal_tukey
for more
capable methods)
weighted_mean_huber(x, w, k, type = "rwm", asym = FALSE, info = FALSE,
na.rm = FALSE, verbose = TRUE, ...)
weighted_total_huber(x, w, k, type = "rwm", asym = FALSE, info = FALSE,
na.rm = FALSE, verbose = TRUE, ...)
weighted_mean_tukey(x, w, k, type = "rwm", info = FALSE, na.rm = FALSE,
verbose = TRUE, ...)
weighted_total_tukey(x, w, k, type = "rwm", info = FALSE, na.rm = FALSE,
verbose = TRUE, ...)
The return value depends on info
:
info = FALSE
:estimate of mean or total [double]
info = TRUE
:a [list]
with items:
characteristic
[character]
,
estimator
[character]
,
estimate
[double]
,
variance
(default: NA
),
robust
[list]
,
residuals
[numeric vector]
,
model
[list]
,
design
(default: NA
),
[call]
[numeric vector]
data.
[numeric vector]
weights (same length as x
).
[double]
robustness tuning constant
(\(0 < k \leq \infty\)).
[character]
type of method: "rwm"
or
"rht"
; see below (default: "rwm"
).
[logical]
toggle for asymmetric Huber psi-function
(default: FALSE
).
[logical]
indicating whether additional information
should be returned (default: FALSE
).
[logical]
indicating whether NA
values should
be removed before the computation proceeds (default: FALSE
).
[logical]
indicating whether additional
information is printed to the console (default: TRUE
).
additional arguments passed to the method (e.g.,
maxit
: maxit number of iterations, etc.).
By default, the method assumes a maximum number of maxit = 100
iterations and a numerical tolerance criterion to stop the iterations of
tol = 1e-05
. If the algorithm fails to converge, you may
consider changing the default values; see svyreg_control
.
Population mean or total. Let \(\mu\) denote the estimated population mean; then, the estimated total is given by \(\hat{N} \mu\) with \(\hat{N} =\sum w_i\), where summation is over all observations in the sample.
Two methods/types are available for estimating the location \(\mu\):
type = "rwm" (default)
:robust weighted
M-estimator of the population mean and total,
respectively. This estimator is recommended for sampling
designs whose inclusion probabilities are not
proportional to some measure of size. [Legacy note: In an
earlier version, the method type = "rwm"
was called
"rhj"
; the type "rhj"
is now silently
converted to "rwm"
]
type = "rht"
:robust Horvitz-Thompson M-estimator of the population mean and total, respectively. This estimator is recommended for proportional-to-size sampling designs.
See the related but more capable functions:
svymean_huber
and
svymean_tukey
,
svytotal_huber
and
svytotal_tukey
.
By default, the Huber
or Tukey
psi-function are used in the specification of the M-estimators. For
the Huber estimator, an asymmetric version of the Huber
psi-function can be used by setting the argument
asym = TRUE
in the function call.
Hulliger, B. (1995). Outlier Robust Horvitz-Thompson Estimators. Survey Methodology 21, 79--87.
Overview (of all implemented functions)
head(workplace)
# Robust Horvitz-Thompson M-estimator of the population total
weighted_total_huber(workplace$employment, workplace$weight, k = 9,
type = "rht")
# Robust weighted M-estimator of the population mean
weighted_mean_huber(workplace$employment, workplace$weight, k = 12,
type = "rwm")
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