split

node

data

is the estimating equation used to model the data in each node

e_equ

is the function that should be used to fit the model in each
node. The function should

e_fn

function taking a numeric vector and returning the estimated loss

l_fn

vector of string names for variables to consider for splitting

the sample weights for each observation

weights

lable of the strata containing the observation

strata

lable of the clusters containing the observation

clusters

integer specifying the minimum number of observations each
node must contain

bin_size

integer specifying the number of permuations

perm_reps

numeric p-value used to reject null hypothesis in permutation 
test

pval

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.

split: split

Description

Usage

Arguments

Value