All functions

calcCriterion()

Evaluate fitted NEMoE obejct

calcdf()

Calculate degree of freedom

calcLL()

Cpp function: calculate the four type of log likelihood function (observed likelihood, penalized likelihood, complete likelihood, penalized complete likelihood) in all levels.

calcProb()

Cpp function: Calculate the estimated probability using softmax function (multinomial regression).

check_validity()

check validity

compLikeli()

Cpp function: Complete likelihood function of mixture distribution

compTransform()

Transformation of compositional data

createCVList()

Create list of parameters for cross validate NEMoE

createParameterList()

Create list of parameters for fitting NEMoE

cvNEMoE()

Parameters tunning in NEMoE

cvtLabel()

Convert label to factor of matrix

filterComp()

Filter the composition matrix

fitNEMoE()

Fit NEMoE model

fitNEMoE0()

Cpp function: fitting NEMoE paramters. (observed likelihood, penalized likelihood, complete likelihood, penalized complete likelihood) in all levels.

genNEMoE()

Generate mixture distribution data

getCoef()

Get coefficients of fitted NEMoE object

getLL()

Get Likelihood of fitted NEMoE object

NEMoE-class

NEMoE class

NEMoE_buildFromList()

Build NEMoE object from list, dataframe or matrix

NEMoE_buildFromPhyloseq()

Build NEMoE object from a phyloseq object.

NEMoE_example

An example of fitted NEMoE object

NEMoE_predict()

Make predictions from a fitted "NEMoE" object.

PD

16S gut microbiome Parkinson's disease dataset

plotExperts()

Plot experts network

plotGating()

Plot gating network

predProb()

Cpp function: Predict probability of mixture distribution

psGather()

Transformation of phyloseq data

rDirichlet()

Cpp function: Sample from a Dirichlet distribution

rSample()

Cpp function: Sample from Categorical distribution

setParam()

Set parameters of fitting NEMoE object

sMulti()

Cpp function: fitting sparse multinomial regression.