Recursive Partitioning for Modeling Survey Data
Description
Fits a linear model to survey data in each node obtained by
recursively partitioning the data. The splitting variables and splits
selected are obtained using a procedure which adjusts for complex sample
design features used to obtain the data. Likewise the model fitting
algorithm produces design-consistent coefficients to the least squares
linear model between the dependent and independent variables.
The first stage of the design is accounted for in the provided variance
estimates. The main function returns the resulting binary tree with the
linear model fit at every end-node. The package provides a number of
functions and methods for these trees.