hdeffsev {VGAM} | R Documentation |
Hauck-Donner Effect: Severity Measures
Description
Computes the severity of the Hauck-Donner effect for each regression coefficient of a fitted VGLM.
Usage
hdeffsev(object, hdiff = 0.005, eta0 = 0,
subset = NULL, maxderiv = 6,
severity.table = c("None", "Faint", "Weak",
"Moderate", "Strong", "ExtremeI",
"ExtremeII", "ExtremeIII",
"ExtremeIV+", "Undetermined"),
lookup = c(0, 0.5, 0.7, 1, 1.3, 2:5),
tx.some = TRUE, wsdmvec = NULL, ...)
Arguments
object |
A fitted |
eta0 , subset , hdiff |
Fed into |
maxderiv , ... |
Fed into |
severity.table |
Character vector of descriptors, plus
the last value for initialization.
Usually users should not assign anything to
this argument.
Used in conjunction with |
lookup |
Numeric, thresholds used for assigning
|
tx.some |
Logical, transform WSDM before comparisons?
Applies to certain links only
(and if |
wsdmvec |
The WSDM statistics can be inputted directly into the function here. |
Details
This function is intended to replace all
previous code for measuring HDE severity.
In particular,
hdeffsev0
and
hdeffsev2
are old and are
not recommended.
Details behind this function spring from
wsdm
.
Value
By default this function
(hdeffsev
)
returns a labelled vector with
names names(coef(object))
and
elements selected from
severity.table
.
Warning
For VGAM version 1.1-13,
hdeffsev()
was renamed to hdeffsev0()
,
hdeffsev2()
to hdeffsev2()
[no change],
and hdeffsev()
is new and based on wsdm(vglmfit)
.
Note
This function has not been tested
extensively and the thresholds may change
slightly in the future.
Improvements are intended.
The function was written specifically for
binomialff
, but they should work
for almost all other family functions.
Author(s)
Thomas W. Yee.
References
Yee, T. W. (2022). On the Hauck-Donner effect in Wald tests: Detection, tipping points and parameter space characterization, Journal of the American Statistical Association, 117, 1763–1774. doi:10.1080/01621459.2021.1886936.
See Also
seglines
,
hdeff
,
hdeffsev0
,
wsdm
which is superior.
Examples
example(genpoisson0)
summary(gfit0, wsdm = TRUE)
hdeffsev(gfit0)