valse (version 0.1-0)

runValse: runValse

Description

Main function

Usage

runValse(
  X,
  Y,
  procedure = "LassoMLE",
  selecMod = "DDSE",
  gamma = 1,
  mini = 10,
  maxi = 50,
  eps = 1e-04,
  kmin = 2,
  kmax = 3,
  rank.min = 1,
  rank.max = 5,
  ncores_outer = 1,
  ncores_inner = 1,
  thresh = 1e-08,
  grid_lambda = numeric(0),
  size_coll_mod = 50,
  fast = TRUE,
  verbose = FALSE,
  plot = TRUE
)

Arguments

X

matrix of covariates (of size n*p)

Y

matrix of responses (of size n*m)

procedure

among 'LassoMLE' or 'LassoRank'

selecMod

method to select a model among 'DDSE', 'DJump', 'BIC' or 'AIC'

gamma

integer for the power in the penaly, by default = 1

mini

integer, minimum number of iterations in the EM algorithm, by default = 10

maxi

integer, maximum number of iterations in the EM algorithm, by default = 100

eps

real, threshold to say the EM algorithm converges, by default = 1e-4

kmin

integer, minimum number of clusters, by default = 2

kmax

integer, maximum number of clusters, by default = 10

rank.min

integer, minimum rank in the low rank procedure, by default = 1

rank.max

integer, maximum rank in the low rank procedure, by default = 5

ncores_outer

Number of cores for the outer loop on k

ncores_inner

Number of cores for the inner loop on lambda

thresh

real, threshold to say a variable is relevant, by default = 1e-8

grid_lambda,

a vector with regularization parameters if known, by default numeric(0)

size_coll_mod

(Maximum) size of a collection of models, by default 50

fast

TRUE to use compiled C code, FALSE for R code only

verbose

TRUE to show some execution traces

plot

TRUE to plot the selected models after run

Value

The selected model (except if the collection of models has less than 11 models, the function returns the collection as it can not select one using Capushe)

Examples

# NOT RUN {
n = 50; m = 10; p = 5
beta = array(0, dim=c(p,m,2))
beta[,,1] = 1
beta[,,2] = 2
data = generateXY(n, c(0.4,0.6), rep(0,p), beta, diag(0.5, p), diag(0.5, m))
X = data$X
Y = data$Y
res = runValse(X, Y, kmax = 5, plot=FALSE)
X <- matrix(runif(100), nrow=50)
Y <- matrix(runif(100), nrow=50)
res = runValse(X, Y, plot=FALSE)

# }