lavaPenalty.estimate.hook: Hook to estimate a penalized lvm model

In bozenne/lava.penalty: Penalized Latent Variable Models

Description

Add LP to dataset, update the estimator for handling LP, and find initialisation.

Usage

lavaPenalty.estimate.hook(x, data, ...)

Examples

m <- lvm()
m <- regression(m,y='y1',x='x'%++%1:2)
m <- regression(m,y='y1',x='z'%++%1:5)

# simul
set.seed(10)
d <- sim(m,5e2)
d <- as.data.frame(scale(d))

suppressWarnings(
start <- coef(estimate(m, data = d, control = list(iter.max = 0)))
)

# penalized lvm 
mp <- penalize(m)
system.time(
lassoLVM <- estimate(mp, data = d, lambda1 = 10, control = list(trace = 2, start = start[coef(mp)], iter.max = 1), estimator = "gaussian2")
)


# reduced penalized lvm
mp.red <- reduce(mp)
system.time(
lassoRLVM <- estimate(mp.red, data = d, lambda1 = 10, control = list(trace = 2, start = start[coef(mp.red)], iter.max = 1))
)

coef(lassoRLVM)-coef(lassoLVM)[names(coef(lassoRLVM))]
lassoRLVM$opt$iterations

bozenne/lava.penalty documentation built on May 13, 2019, 1:41 a.m.