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Non-normal linear regression inspired by Box-Cox models
BoxCox(formula, data, subset, weights, offset, cluster, na.action = na.omit, ...)An object of class BoxCox, with corresponding coef,
vcov, logLik, estfun, summary,
print, plot and predict methods.
an object of class "formula": a symbolic description
of the model structure to be
fitted. The details of model specification are given under
tram and in the package vignette.
an optional data frame, list or environment (or object
coercible by as.data.frame to a data frame) containing the
variables in the model. If not found in data, the
variables are taken from environment(formula).
an optional vector specifying a subset of observations to be used in the fitting process.
an optional vector of weights to be used in the fitting
process. Should be NULL or a numeric vector. If present,
the weighted log-likelihood is maximised.
this can be used to specify an _a priori_ known component to
be included in the linear predictor during fitting. This
should be NULL or a numeric vector of length equal to the
number of cases.
optional factor with a cluster ID employed for computing clustered covariances.
a function which indicates what should happen when the data
contain NAs. The default is set to na.omit.
additional arguments to tram.
A normal model for transformed responses, where the transformation is estimated from the data simultaneously with the regression coefficients. This is similar to a Box-Cox transformation, but the technical details differ. Examples can be found in the package vignette.
The model is defined with a negative shift term. Large values of the linear predictor correspond to large values of the conditional expectation response (but this relationship is potentially nonlinear).
Torsten Hothorn, Lisa Moest, Peter Buehlmann (2018), Most Likely Transformations, Scandinavian Journal of Statistics, 45(1), 110--134, 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)
BoxCox(cmedv ~ chas + crim + zn + indus + nox +
rm + age + dis + rad + tax + ptratio + b + lstat,
data = BostonHousing2)
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