class_svystat_rob {robsurvey} | R Documentation |
Utility Functions for Objects of Class svystat_rob
Description
Methods and utility functions for objects of class svystat_rob
.
Usage
mse(object)
## S3 method for class 'svystat_rob'
summary(object, digits = max(3L,
getOption("digits") - 3L), ...)
## S3 method for class 'svystat_rob'
coef(object, ...)
## S3 method for class 'svystat_rob'
SE(object, ...)
## S3 method for class 'svystat_rob'
vcov(object, ...)
## S3 method for class 'svystat_rob'
scale(x, ...)
## S3 method for class 'svystat_rob'
residuals(object, ...)
## S3 method for class 'svystat_rob'
fitted(object, ...)
robweights(object)
## S3 method for class 'svystat_rob'
robweights(object)
## S3 method for class 'svystat_rob'
print(x, digits = max(3L, getOption("digits") - 3L), ...)
Arguments
object |
object of class |
digits |
|
... |
additional arguments passed to the method. |
x |
object of class |
Details
Package survey must be attached to the search path in order to use
the functions (see library
or require
).
Utility functions:
-
mse
computes the estimated risk (mean square error) in presence of representative outliers; see alsomer
-
summary
gives a summary of the estimation properties -
robweights
extracts the robustness weights -
coef
extracts the estimate of location -
SE
extracts the (estimated) standard error -
vcov
extracts the (estimated) covariance matrix -
residuals
extracts the residuals -
fitted
extracts the fitted values
See Also
svymean_dalen
, svymean_huber
,
svymean_ratio
, svymean_reg
,
svymean_tukey
, svymean_trimmed
,
svymean_winsorized
svytotal_dalen
, svytotal_huber
,
svytotal_ratio
, svytotal_reg
,
svytotal_tukey
, svytotal_trimmed
,
svytotal_winsorized
Examples
head(workplace)
library(survey)
# Survey design for stratified simple random sampling without replacement
dn <- if (packageVersion("survey") >= "4.2") {
# survey design with pre-calibrated weights
svydesign(ids = ~ID, strata = ~strat, fpc = ~fpc, weights = ~weight,
data = workplace, calibrate.formula = ~-1 + strat)
} else {
# legacy mode
svydesign(ids = ~ID, strata = ~strat, fpc = ~fpc, weights = ~weight,
data = workplace)
}
# Estimated one-sided k winsorized population total (i.e., k = 2 observations
# are winsorized at the top of the distribution)
wtot <- svytotal_k_winsorized(~employment, dn, k = 2)
# Show summary statistic of the estimated total
summary(wtot)
# Estimated mean square error (MSE)
mse(wtot)
# Estimate, std. err., variance, and the residuals
coef(wtot)
SE(wtot)
vcov(wtot)
residuals(wtot)
# M-estimate of the total (Huber psi-function; tuning constant k = 3)
mtot <- svytotal_huber(~employment, dn, k = 45)
# Plot of the robustness weights of the M-estimate against its residuals
plot(residuals(mtot), robweights(mtot))