mcl_step: mcl_step

In aplantin/MCL: Fits multilevel compositional lasso

Description

Calculates MCL coefficient estimates over a grid of (lam1, lam2) pairs

Usage

mcl_step(Z, W, y, mu = 1, groups, step = 0.1, lam.seq = NULL,
  lam.max = NULL, nlam = c(10, 10), min.frac = 0.1, maxit = 10000,
  thresh = 1e-04, std = TRUE, verbose = FALSE)

Arguments

Z	Otu matrix at group level
W	Otu matrix within groups
y	Outcome vector
mu	Lagrange scaling parameter; default 1
groups	Vector of group membership per feature
step	Step-size; default 0.1
lam.seq	Sequence of lambda values; default NULL
lam.max	Maximum lambda value; default NULL
nlam	Vector of length 2 indicating number of lambda values to test for lam1 and lam2; default (10, 10)
min.frac	Fraction of max.lam that the minimum lambda value should be; default 0.01
maxit	Maximum number of iterations; default 10000
thresh	Threshold for convergence; default 0.0001
std	Logical indicating whether data should be standardized; default TRUE
verbose	Print lambdas as indicator of progress?; default FALSE

Value

List with intercept vector, beta matrix (q x (nlam1 x nlam2)), gamma matrix (p x (nlam1 x nlam2)), lambda sequence (list: lam1, lam2)

aplantin/MCL documentation built on May 25, 2019, 2:26 p.m.