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The function transforms the dependent variable of a linear model using the Square-root shift transformation. The transformation parameter can either be estimated using different estimation methods or given.
sqrtshift(object, lambda = "estim", method = "ml",
lambdarange = NULL, plotit = TRUE)
an object of type lm.
either a character named "estim" if the optimal transformation parameter should be estimated or a numeric value determining a given value for the transformation parameter. Defaults to "estim".
a character string. Different estimation methods can be used for the estimation of the optimal transformation parameter: (i) Maximum likelihood approach ("ml"), (ii) Skewness minimization ("skew"), (iii) Kurtosis optimization ("kurt"), (iv) Divergence minimization by Kolmogorov-Smirnov ("div.ks"), by Cramer-von-Mises ("div.cvm") or by Kullback-Leibler ("div.kl"). Defaults to "ml".
a numeric vector with two elements defining an interval
that is used for the estimation of the optimal transformation parameter.
Defaults to NULL
. In this case the lambdarange is set to the range
of the data. In case the lowest value is negative the absolute value of the
lowest value plus 1 is the lower bound for the range.
logical. If TRUE
, a plot that illustrates the optimal
transformation parameter or the given transformation parameter is returned.
Defaults to TRUE
.
An object of class trafo
. Methods such as
as.data.frame.trafo
and print.trafo
can
be used for this class.
# NOT RUN {
# Load data
data("cars", package = "datasets")
# Fit linear model
lm_cars <- lm(dist ~ speed, data = cars)
# Transform dependent variable using a maximum likelihood approach
sqrtshift(object = lm_cars, plotit = TRUE)
# }
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