plot_netcox_cv: plots for 'netcox_cv'

In netcox: Structural Learning in Cox Models with Time-Dependent Covariates

plots for netcox_cv

Description

Plot the cross-validation curves produced by netcox_cv.

Usage

plot_netcox_cv(netcox_cv_obj)

Arguments

netcox_cv_obj

The netcox_cv object.

Value

The plot is the cvm (red dot) for each lambda with its standard error (vertical bar). The two vertical dashed lines corresponds to the lambda.min and lambda.1se

See Also

netcox, netcox_cv.

Examples

grp <- matrix(c(0, 0, 0, 0, 0,
                0, 0, 0, 0, 0,
                1, 1, 0, 0, 0,
                0, 0, 0, 0, 0,
                0, 1, 0, 1, 0),
              ncol = 5, byrow = TRUE)
grp.var <- matrix(c(1, 0, 0, 0, 0, #A1
                    1, 0, 0, 0, 0, #A2
                    0, 0, 0, 1, 0, #C1
                    0, 0, 0, 1, 0, #C2
                    0, 1, 0, 0, 0, #B
                    0, 0, 1, 0, 0, #A1B
                    0, 0, 1, 0, 0, #A2B
                    0, 0, 0, 0, 1, #C1B
                    0, 0, 0, 0, 1  #C2B
                   ), ncol = 5, byrow = TRUE)
eta_g <- rep(1, 5)
x <- as.matrix(sim[, c("A1","A2","C1","C2","B",
                       "A1B","A2B","C1B","C2B")])
lam.seq <- 10^seq(0, -2, by = -0.2)

cv <- netcox_cv(x = x,
                ID = sim$Id,
                time = sim$Start,
                time2 = sim$Stop,
                event = sim$Event,
                lambda = lam.seq,
                group = grp,
                group_variable = grp.var,
                penalty_weights = eta_g,
                nfolds = 5,
                tol = 1e-4,
                maxit = 1e3,
                verbose = FALSE)
plot_netcox_cv(cv)               

netcox documentation built on March 7, 2023, 6:15 p.m.