summary.DSA {DSA} | R Documentation |
Provides a useful summary of a call to the DSA routine.
summary.DSA(object, ...)
object |
an object of class 'DSA'. |
... |
currently ignored. |
An object of class 'summary.DSA'. Objects of class 'summary.DSA' have the following attributes:
model.selected |
a formula representing the final model selected by the DSA routine. |
family |
a description of the link function for model.selected : gaussian indicates
the indentity function while binomial indicates the logit function. |
n.obs |
number of observations in the data frame data passed in to the DSA routine. |
n.nonna |
number of complete observations on which model.selected
is based (no missing values). |
best.average.CVrisk |
minimum average cross-validated risk among all average cross-validated risks associated with all model sizes, interaction orders and dimension reduction levels considered by the DSA routine. |
coefficients |
the coefficients of model.selected fitted on
n.nonna observations from the learning set. |
io.and.size |
the 'best' model size and order of interaction selected by cross-validation |
average.CVrisk.model.selected |
average cross-validated risk
for model.selected . |
n.id |
number of independent experimental units in the data frame
data passed in to the DSA routine. |
n.id.nonna |
number of complete independent experimental units on which model.selected
is based (no missing values). |
nselected.vars |
the number of candidate variables after dimension reduction based on a user-specified rank cut-off or a rank cut-off selected by cross-validation. |
ncandidate.vars |
the number of candidate variables truly
considered, i.e. the number of variables whose ranks are lower than or equal to the largest cut-off
value in rank.cutoffs . |
n.vars |
the number of candidate variables considered pre-dimension reduction. |
rank.cutoffs |
the rank cut-offs considered. |
best.rank.cutoff |
NULL if the dimension reduction level
is user-specified or the 'best' dimension reduction level if the
dimension reduction step is based on cross-validation. |
formula |
the original base formula passed in to the DSA routine. |
moves |
a logical vector indicating whether deletion and substitution moves where permitted or inhibited in the model search. |
James Bullard.
DSA
.
library(DSA) ## an example using the state census data. (gaussian) data(state) state.data <- as.data.frame(state.x77) colnames(state.data) <- unlist(lapply(strsplit(colnames(state.data), " "), function(x) paste(x, collapse = ""))) res <- DSA(Murder ~ 1, data = state.data, maxsize = 5, maxsumofpow = 2,maxorderint = 2) res summary(res)