cv.lori: selection of the regularization parameters (lambda1 and...

In genevievelrobin/lori: Low-Rank Interactions in Count Data with Covariates

Description

selection of the regularization parameters (lambda1 and lambda2) of the lori function by cross-validation

Usage

cv.lori(Y, cov = NULL, intercept = F, reff = T, ceff = T,
  rank.max = 10, N = 5, len = 20, prob = 0.2, algo = c("alt",
  "mcgd"), thresh = 1e-06, maxit = 100, trace.it = F, parallel = F)

Arguments

Y	[matrix, data.frame] abundance table (nxp)
cov	[matrix, data.frame] design matris (npxq)
intercept	[boolean] whether an intercept should be fitted, default value is FALSE
reff	[boolean] whether row effects should be fitted, default value is TRUE
ceff	[boolean] whether column effects should be fitted, default value is TRUE
rank.max	[integer] maximum rank of interaction matrix, default is 2
N	[integer] number of cross-validation folds
len	[integer] the size of the grid
prob	[numeric in (0,1)] the proportion of entries to remove for cross-validation
algo	type of algorithm to use, either one of "mcgd" (mixed coordinate gradient descent, adapted to large dimensions) or "alt" (alternating minimization, adapted to small dimensions)
thresh	[positive number] convergence threshold, default is 1e-5
maxit	[integer] maximum number of iterations, default is 100
trace.it	[boolean] whether information about convergence should be printed
parallel	[boolean] whether the N-fold cross-validation should be parallelized, default value is TRUE

Value

A list with the following elements

lambda1	regularization parameter estimated by cross-validation for nuclear norm penalty (interaction matrix)
lambda2	regularization parameter estimated by cross-validation for l1 norm penalty (main effects)
errors	a table containing the prediction errors for all pairs of parameters

Examples

X <- matrix(rnorm(20), 10)
Y <- matrix(rpois(10, 1:10), 5)
res <- cv.lori(Y, X, N=2, len=2)

genevievelrobin/lori documentation built on May 17, 2019, 11:14 p.m.