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norm (version 1.0-11.1)

Analysis of Multivariate Normal Datasets with Missing Values

Description

An integrated set of functions for the analysis of multivariate normal datasets with missing values, including implementation of the EM algorithm, data augmentation, and multiple imputation.

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Install

install.packages('norm')

Monthly Downloads

19,711

Version

1.0-11.1

License

GPL (>= 2)

Maintainer

John Fox

Last Published

June 18th, 2023

Functions in norm (1.0-11.1)

ninvwish

Random normal-inverted Wishart variate
prelim.norm

Preliminary manipulations for a matrix of incomplete continuous data.
imp.norm

Impute missing multivariate normal data
loglik.norm

Observed-data loglikelihood for normal data
em.norm

EM algorithm for incomplete normal data
rngseed

Initialize random number generator seed
logpost.norm

Observed-data log-posterior for normal data
da.norm

Data augmentation for incomplete multivariate normal data
getparam.norm

Extract normal parameters from packed storage
mdata

Dataset with missing values to illustrate use of package norm
.code.to.na

Changes missing value code to NA
mda.norm

Monotone data augmentation for incomplete multivariate normal data
makeparam.norm

Convert normal parameters to packed storage
mi.inference

Multiple imputation inference
.na.to.snglcode

Changes NA's to single precision missing value code