EM.normal: EM for multivariate normal data

In martinSter/modi: Multivariate Outlier Detection and Imputation for Incomplete Survey Data

EM for multivariate normal data

Description

This version of EM does not contain the computation of the observed sufficient statistics, they will be computed in the main program of BEM and passed as parameters as well as the statistics on the missingness patterns.

Usage

EM.normal(
  data,
  weights = rep(1, nrow(data)),
  n = sum(weights),
  p = ncol(data),
  s.counts,
  s.id,
  S,
  T.obs,
  start.mean = rep(0, p),
  start.var = diag(1, p),
  numb.it = 10,
  Estep.output = FALSE
)

Arguments

data	matrix or dataframe with data.
weights	vector of weights.
n	number of rows.
p	number of columns.
s.counts	s.counts.
s.id	s.id.
S	S.
T.obs	T.obs.
start.mean	initial center.
start.var	initial variance.
numb.it	numb.it.
Estep.output	Estep.output.

Author(s)

Beat Hulliger

martinSter/modi documentation built on March 14, 2023, 12:09 p.m.