TauAndParameters_EstParmFunc_FBM: Obtaining the value of tau and the estimate value of the rest...

In CoDaLoMic: Compositional Models to Longitudinal Microbiome Data

Obtaining the value of tau and the estimate value of the rest of the parameters

Description

This function estimates the parameters of the FBM model.

Usage

TauAndParameters_EstParmFunc_FBM(
  ttau = 30,
  ridge.final,
  Iter.EstParmFunc = 80,
  especie,
  EspecieMaxima,
  Tt,
  E,
  seed = NULL
)

Arguments

ttau	Number. We estimate de FBM model for the values of tau: 1, 2,..., ttau
ridge.final	Object of class "ridgelm". Values obtained with the ridge regression.
Iter.EstParmFunc	Number. Number of iterations. Default: 80 iterations.
especie	Matrix that contains at row i the bacterial taxa of bacteria i at all time points. The bacteria placed in the last row of the matrix will be used as reference in the alr transformation and will be at the denominator of the balance.
EspecieMaxima	Row in which the bacteria used as reference is in especie. This is the bacteria that is going to be at the denominator of the balance and at the denominator of the alr transformartion. As a result, in this function, EspecieMaxima must be equal to E
Tt	Number of time points available
E	Number. Number of bacteria available.
seed	Number. Set a seed. Default seed=NULL.

Details

We give to the parameter tau the value 1,2,...,ttau. We estimate the FBM model for all this values (using the function "Estimate_param_FBM") and we select the value of tau that minimizes the AIC. The regression of this model is defined by

\mu_{it}=a_{i1}+a_{i2}\cdot\text{alr}(x_{i,(t-1)})+a_{i3}\cdot\text{Balance}(x_{i,(t-1)})\text{ for }i=1,\dots, D-1\text{ where } D \text{ is the number of bacteria}

Value

Returns a list with:

• EstimateParameters: Vector with the estimated parameters, in the following order: a11,a12,a13, a21, a22,a23, ...a(D-1)1,a(D-1)2,a(D-1)3,tau. Where D is the number of bacterial species present in the matrix especie.

• AIC Number: Value of the AIC.

• All.iter: Matrix. Each row has the parameters obtained in each iteration. The parameters are in the columns written in the same order that they are written in Param.Estimates . In this matrix we must observe that in the last iterations the values has really similar or equal values, if not, we need to increase the value of Iter.EstParmFunc.

References

Creus-Martí, I., Moya, A., Santonja, F. J. (2021). A Dirichlet autoregressive model for the analysis of microbiota time-series data. Complexity, 2021, 1-16.

Examples

set.seed(123)
especie=t(gtools::rdirichlet(5,c(1,3,1)))
Tt=5
E=3
EspecieMaxima=3
ridge.final=ridgeregression(Tt,especie, E, EspecieMaxima)
ttau=10
Iter.EstParmFunc=10

TauAndParameters_EstParmFunc_FBM(ttau,ridge.final,Iter.EstParmFunc, especie,EspecieMaxima,Tt,E,714)

CoDaLoMic documentation built on April 12, 2025, 2:18 a.m.