norm2-package {norm2} | R Documentation |
Functions for estimation and multiple imputation from incomplete multivariate data under a normal model
The norm2
package provides functions for analyzing incomplete
multivariate
data using techniques and algorithms described by Schafer (1997). The
name of this package derives from the assumed model for the complete
data, which is a multivariate normal model. The
major functions are:
emNorm EM algorithm estimating model parameters mcmcNorm MCMC algorithm for simulating parameters and missing values impNorm Simulate or predict missing values loglikNorm Loglikelihood function logpostNorm Log-posterior density function miInference Combine results from analyses after multiple imputation
The package also includes three datasets:
cholesterol Cholesterol levels for heart-attack patients flas Foreign Language Attitude Scale marijuana Changes in heart rate after marijuana use
Fortran source code written by the author for a much earlier version
called norm
was ported to an R package by Alvaro A. Novo and
distributed through the Comprehensive R Archive
Network (CRAN). The old package norm
is still available on
CRAN, but it has some
major limitations (e.g., it does not work reliably when the number of
variables exceeds 30) and the author does not recommend its use.
Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Maintainer: Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Schafer, J.L. (1997) Analysis of Incomplete Multivariate
Data. London: Chapman & Hall/CRC Press.
For more information about functions in
norm2
, see User's Guide for norm2
in the library subdirectory doc
.