nm_fit: Log-ratio normal-multinomial parameters estimation.

Description Usage Arguments Value Examples

View source: R/fitting.R

Description

The parameters mu and sigma are expressed with respect basis given by function @ilrBase.

Usage

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nm_fit(X, eps = 0.001, nsim = 1000, parallel.cluster = NULL,
  max.em.iter = 100, min.em.iter = 10, expected = TRUE, verbose = FALSE,
  init.method = "dm", development = FALSE)

Arguments

X

count data set

eps

maximum error accepted on the last EM-step

nsim

number of simulations used in the E-step

parallel.cluster

parallel Socket Cluster created with function @makeCluster

max.em.iter

maximum number of steps allowed in the EM-algorithm

min.em.iter

minimum number of steps before allowing to double the number of iterations

expected

if TRUE the expected probabilities are returned (default:TRUE)

verbose

show information during estimation

init.method

how to initiate the method (default 'dm' initiating with dirichlet-multinomial estimation). Another options are: 'aitchison', 'bootstrap'. Initiating with aproximation from raw data and using bootstrapping respectively. For stability, we recommend to use 'dm' method.

development

show diagnostic messages

Value

A list with parameters mu and sigma and the number of iterations before convergence

Examples

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X = rnormalmultinomial(100, 100, rep(0,4), diag(4))
nm_fit(X, verbose = T)

mcomas/normalmultinomial documentation built on May 22, 2017, 1:14 a.m.