boxcox
function in the boxCox(object, ...)
## S3 method for class 'default':
boxCox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp = (plotit && (m < 100)), eps = 1/50,
xlab = expression(lambda),
ylab = "log-Likelihood", family="bcPower", grid=TRUE, ...)
## S3 method for class 'formula':
boxCox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp = (plotit && (m < 100)), eps = 1/50,
xlab = expression(lambda),
ylab = "log-Likelihood", family="bcPower", ...)
## S3 method for class 'lm':
boxCox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp = (plotit && (m < 100)), eps = 1/50,
xlab = expression(lambda),
ylab = "log-Likelihood", family="bcPower", ...)
lm
and aov
objects are handled.TRUE
.TRUE
if plotting with lambda of length less than 100."lambda"
."log-Likelihood"
."bcPower"
for the Box-Cox power family of
transformations. If set to "yjPower"
the Yeo-Johnson family, which
permits negative responses, is used.plotit=TRUE
plots log-likelihood vs
lambda and indicates a 95lambda. If interp=TRUE
, spline interpolation is used to give a smoother plot.boxcox
function in the
family
and grid
are
identical, and if the arguments
family = "bcPower", grid=FALSE
is set it gives an identical graph. If
family = "yjPower"
then the Yeo-Johnson power transformations, which
allow nonpositive responses, will be used.boxcox
, yjPower
, bcPower
,
powerTransform
boxCox(Volume ~ log(Height) + log(Girth), data = trees,
lambda = seq(-0.25, 0.25, length = 10))
data("quine", package = "MASS")
boxCox(Days ~ Eth*Sex*Age*Lrn, data = quine,
lambda = seq(-0.05, 0.45, len = 20), family="yjPower")
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