box.tidwell {car} | R Documentation |
Computes the Box-Tidwell power transformations of the predictors in a linear model.
box.tidwell(y, ...) ## S3 method for class 'formula': box.tidwell(formula, other.x=NULL, data=NULL, subset, na.action=options()$na.action, verbose=FALSE, tol=0.001, max.iter=25, ...) ## Default S3 method: box.tidwell(y, x1, x2=NULL, max.iter=25, tol=0.001, verbose=FALSE, ...) ## S3 method for class 'box.tidwell': print(x, digits, ...)
formula |
two-sided formula, the right-hand-side of which gives the predictors to be transformed. |
other.x |
one-sided formula giving the predictors that are not candidates for transformation, including (e.g.) factors. |
data |
an optional data frame containing the variables in the model.
By default the variables are taken from the environment from which
box.tidwell is called. |
subset |
an optional vector specifying a subset of observations to be used. |
na.action |
a function that indicates what should happen when the data contain NA s.
The default is set by the na.action setting of options . |
verbose |
if TRUE a record of iterations is printed. |
tol |
if maximum relative change in coefficients is less than tol then
convergence is declared. |
max.iter |
maximum number of iterations. |
y |
response variable. |
x1 |
matrix of predictors to transform. |
x2 |
matrix of predictors that are not candidates for transformation. |
... |
not for the user. |
x |
box.tidwell object. |
digits |
number of digits for rounding. |
The maximum-likelihood estimates of the transformation parameters are computed by Box and Tidwell's (1962) method, which is usually more efficient than using a general nonlinear least-squares routine for this problem. Score tests for the transformations are also reported.
an object of class box.tidwell
, which is normally just printed.
John Fox jfox@mcmaster.ca
Box, G. E. P. and Tidwell, P. W. (1962) Transformation of the independent variables. Technometrics 4, 531-550.
Fox, J. (1997) Applied Regression, Linear Models, and Related Methods. Sage.
box.tidwell(prestige~income+education, ~ poly(women,2), data=Prestige) ## income education ## Initial Power -0.91030 2.24354 ## Score Statistic -5.30129 2.40556 ## p-value 0.00000 0.01615 ## MLE of Power -0.03777 2.19283