| regsubsets {leaps} | R Documentation |
Generic function for regression subset selection with methods for formula and matrix arguments.
regsubsets(x=, ...)
## S3 method for class 'formula':
regsubsets(x=, data=, weights=NULL, nbest=1, nvmax=8, force.in=NULL, force.out=NULL, intercept=TRUE, method=c("exhaustive", "backward", "forward", "seqrep"), really.big=FALSE,...)
## Default S3 method:
regsubsets(x=, y=, weights=rep(1, length(y)), nbest=1, nvmax=8,
force.in=NULL, force.out=NULL, intercept=TRUE, method=c("exhaustive",
"backward", "forward", "seqrep"), really.big=FALSE,...)
## S3 method for class 'regsubsets':
summary(object,all.best=TRUE,matrix=TRUE,matrix.logical=FALSE,df=NULL,...)
x |
design matrix or model formula for full model |
data |
Optional data frame |
y |
response vector |
weights |
weight vector |
nbest |
number of subsets of each size to record |
nvmax |
maximum size of subsets to examine |
force.in |
index to columns of design matrix that should be in all models |
force.out |
index to columns of design matrix that should be in no models |
intercept |
Add an intercept? |
method |
Use exhaustive search, forward selection, backward selection or sequential replacement to search. |
really.big |
Must be TRUE to perform exhaustive search on more than 50 variables. |
object |
regsubsets object |
all.best |
Show all the best subsets or just one of each size |
matrix |
Show a matrix of the variables in each model or just summary statistics |
matrix.logical |
With matrix=TRUE, the matrix is logical
TRUE/FALSE or string "*"/code{" "} |
df |
Specify a number of degrees of freedom for the summary
statistics. The default is n-1 |
... |
Other arguments for future methods |
An object of class "regsubsets" containing no user-serviceable parts. It is designed to be processed by summary.regsubsets.
This function improves on leaps in several ways. The design matrix need not be of full rank. The ability to restrict nvmax speeds up exhaustive searches considerably. There is no hard-coded limit to the number of variables.
data(swiss) a<-regsubsets(as.matrix(swiss[,-1]),swiss[,1]) summary(a) b<-regsubsets(Fertility~.,data=swiss) summary(a)