R: Generate a model environment from design and response matrix
ModelEnvMatrix
R Documentation
Generate a model environment from design and response matrix
Description
A simple model environment creator function working off matrices for
input and response. This is much simpler and more limited than
formula-based environments, but faster and easier to use, if only
matrices are allowed as input.
an optional vector specifying a subset of observations to
be used in the fitting process.
na.action
a function which indicates what should happen when the data
contain NA's.
other
an optional named list of additional formulae.
...
currently not used
Details
ModelEnvMatrix returns an object of class
ModelEnv-class - a high level object for storing
data improving upon the capabilities of simple data matrices.
Funny things may happen if the inpiut and response matrices do not have
distinct column names and the data new data are supplied via the
get and set slots.
Value
An object of class ModelEnv-class.
Examples
### use Sepal measurements as input and Petal as response
data(iris)
me <- ModelEnvMatrix(iris[,1:2], iris[,3:4])
me
### extract data from the ModelEnv object
dim(me@get("designMatrix"))
summary(me@get("responseMatrix"))
### subsets and missing values
iris[1,1] <- NA
me <- ModelEnvMatrix(iris[,1:2], iris[,3:4], subset=1:5, na.action=na.omit)
## First case is not complete, so me contains only cases 2:5
me
me@get("designMatrix")
me@get("responseMatrix")
## use different cases
me@set(data=iris[10:20,])
me@get("designMatrix")
## these two should be the same
stopifnot(all.equal(me@get("responseMatrix"), as.matrix(iris[10:20,3:4])))