fit_aitchison: fit_aitchison

In adw96/DivNet: Diversity Estimation in Networked Ecological Communities

fit_aitchison

Description

This function estimates the parameters of the log-ratio model

Usage

fit_aitchison(
  W,
  X = NULL,
  tuning = NULL,
  perturbation = NULL,
  network = NULL,
  base = NULL,
  ncores = NULL,
  ...
)

Arguments

W	count matrix, with columns listing the OTUs and rows listing the samples
X	covariate matrix (optional)
tuning	settings for tuning the MC-MH algorithm. Options include NULL (defaults to "fast"), "fast", "careful" or a named list with components EMiter (number of EM iterations; 6 for fast, 10 for careful), EMburn (number of EM iterations to burn; 3 for fast, 5 for careful), MCiter (number of MC iterations; 500 for fast, 1000 for careful), MCburn (number of MC iterations to burn; 250 for fast, 500 for careful) and stepsize (variance used for MH samples; 0.01 for both fast and careful)
perturbation	size of purturbation for zero counts, defaults to NULL (0.05)
network	How to estimate network. Defaults to NULL (the default), "default" (generalised inverse, aka naive). Other options include "diagonal", "stars" (requires glasso and SpiecEasi to be installed), or a function that you want to use to estimate the network
base	OTU index to be used for base. if NULL, will use most common taxon
ncores	number of cores to use for MH sampling, defaults to 1
...	additional arguments to be supplied to the network function

Author(s)

Bryan Martin

Amy Willis

adw96/DivNet documentation built on Oct. 2, 2023, 11:49 a.m.