Lehmann | R Documentation |
Non-normal linear regression for Lehmann-alternatives
Lehmann(formula, data, subset, weights, offset, cluster, na.action = na.omit, ...)
formula |
an object of class |
data |
an optional data frame, list or environment (or object
coercible by |
subset |
an optional vector specifying a subset of observations to be used in the fitting process. |
weights |
an optional vector of weights to be used in the fitting
process. Should be |
offset |
this can be used to specify an _a priori_ known component to
be included in the linear predictor during fitting. This
should be |
cluster |
optional factor with a cluster ID employed for computing clustered covariances. |
na.action |
a function which indicates what should happen when the data
contain |
... |
additional arguments to |
This transformation model uses the cumulative distribution function for the standard Gumbel maximum extreme value distribution to map the shifted transformation function into probabilities. The exponential of the shift paramater can be interpreted as a Lehmann-alternative or reverse time hazard ratio.
An object of class Lehmann
, with corresponding coef
,
vcov
, logLik
, estfun
, summary
,
print
, plot
and predict
methods.
Erich L. Lehmann (1953), The Power of Rank Tests, The Annals of Mathematical Statistics, 24(1), 23-43.
Torsten Hothorn, Lisa Moest, Peter Buehlmann (2018), Most Likely Transformations, Scandinavian Journal of Statistics, 45(1), 110–134, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/sjos.12291")}.
data("BostonHousing2", package = "mlbench")
lm(cmedv ~ crim + zn + indus + chas + nox + rm + age + dis +
rad + tax + ptratio + b + lstat, data = BostonHousing2)
Lehmann(cmedv ~ chas + crim + zn + indus + nox +
rm + age + dis + rad + tax + ptratio + b + lstat,
data = BostonHousing2)
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