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.
|Depends:||R (≥ 2.10)|
|Imports:||Rcpp (≥ 0.12.3)|
|Author:||daniell toth [aut, cre]|
|Maintainer:||daniell toth <danielltoth at yahoo.com>|
|CRAN checks:||rpms results|
An Introduction to rpms
|Windows binaries:||r-devel: rpms_0.2.0.zip, r-release: rpms_0.2.0.zip, r-oldrel: rpms_0.2.0.zip|
|OS X Mavericks binaries:||r-release: rpms_0.2.0.tgz, r-oldrel: rpms_0.2.0.tgz|
|Old sources:||rpms archive|
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