makeind: Make Model Matrix from Data Frame

In dbarts: Discrete Bayesian Additive Regression Trees Sampler

Make Model Matrix from Data Frame

Description

Converts a data frame with numeric and factor contents into a matrix, suitable for use with bart. Unlike in linear regression, factors containing more than two levels result in dummy variables being created for each level.

Usage

makeModelMatrixFromDataFrame(x, drop = TRUE)
makeind(x, all = TRUE)
makeTestModelMatrix(data, newdata)

Arguments

x	Data frame of explanatory variables.
drop	Logical or list controling whether or not columns that are constants or factor levels with no instances are omitted from the result. When a list, must be of length equal to x. Elements correspond to x according to: vector - single logical matrix - vector of logicals, one per column factor - table of factor levels to be referenced; levels with counts of 0 are to be dropped
all	Not currently implemented.
data	An existing dbartsData object.
newdata	Test data frame.

Details

Character vectors are included as factors. If you have numeric data coded as characters, convert it using as.numeric first.

Note that if you have train and test data frames, it may be best to rbind the two together, apply makeModelMatrixFromDataFrame to the result, and then pull them back apart. Alternatively, save the drop attribute used in creating the training data and use it when creating a matrix from the test data, as in the example given below.

Use of these functions is not required when using bart, bart2, or dbartsSampler; they exist to allow the user finer control and to assist with writing packages that separate the creation of training from test data.

Value

A matrix with columns corresponding to the elements of the data frame. If drop = TRUE or is a list, the attribute drop on the result is set to the list used when creating the matrix.

Author(s)

Vincent Dorie: [e-mail].

Examples

iv <- 1:10
rv <- runif(10)
f <- factor(rep(seq.int(3), c(4L, 4L, 2L)),
            labels = c("alice", "bob", "charlie"))
df <- data.frame(iv, rv, f)

mm <- makeModelMatrixFromDataFrame(df)

## create test and train matrices with disjoint factor levels
train.df <- df[1:8,]
test.df <- df[9:10,]
train.mm <- makeModelMatrixFromDataFrame(train.df)
test.mm <- makeModelMatrixFromDataFrame(test.df, attr(train.mm, "drop"))

dbarts documentation built on May 29, 2024, 3:31 a.m.