fwdsco | R Documentation |
This function applies the forward search approach to the Box-Cox transformation of response in linear regression models.
fwdsco(formula, data, nsamp = "best", lambda = c(-1, -0.5, 0, 0.5, 1), x = NULL, y = NULL, intercept = TRUE, na.action, trace = TRUE)
formula |
a symbolic description of the model to be fit. The details of the model are the same as for lm. |
data |
an optional data frame containing the variables in the model. By default the variables are taken from the environment from which the function is called. |
nsamp |
the initial subset for the forward search in linear regression is found by fitting the regression model with the R function |
lambda |
a vector (or a single numerical value) of lambda values for the response transformation. |
x |
A matrix of predictors values (if no formula is provided). |
y |
A vector of response values (if no formula is provided). |
intercept |
Logical for the inclusion of the intercept (if no formula is provided). |
na.action |
a function which indicates what should happen when the data contain |
trace |
logical, if |
The function returns an object of class"fwdsco"
with the following components:
call |
the matched call. |
Likelihood |
a ((n-p+1) x n.lambda) matrix of likelihood values. |
ScoreTest |
a ((n-p+1) x n.lambda) matrix of score test statistic values. |
Unit |
a list with an element for each lambda values. Each element provides a matrix of units added (to a maximum of 5 units) at each step of the forward search. |
Input |
a list with n, p and the vector of lambda values used. |
x |
The design matrix. |
y |
The vector for the response. |
Originally written for S-Plus by:
Kjell Konis kkonis@insightful.com and Marco Riani mriani@unipr.it
Ported to R by Luca Scrucca luca@stat.unipg.it
Atkinson, A.C. and Riani, M. (2000), Robust Diagnostic Regression Analysis, First Edition. New York: Springer, Chapter 4.
summary.fwdsco
, plot.fwdsco
, fwdlm
, fwdglm
.
data(wool) mod <- fwdsco(y ~ x1 + x2 + x3, data = wool) summary(mod) plot(mod, plot.mle=FALSE) plot(mod, plot.Sco=FALSE, plot.Lik=TRUE)
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