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. |