plot_netcox_sp: plots for 'netcox' and 'netcox_cv'

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

plots for netcox and netcox_cv

Description

Plot the solution path produced by netcox or netcox_cv.

Usage

plot_netcox_sp(
  netcox_obj,
  plot_min = FALSE,
  plot_1se = FALSE,
  type = "l",
  log = "x",
  ...
)

Arguments

netcox_obj	The netcox or netcox_cv object.
plot_min	Logical, whether a vertical line at lambda.min acquired by netcox_cv is plotted. Not available if netcox_obj is a netcox fit.
plot_1se	Logical, whether a vertical line at lambda.1se acquired by netcox_cv is plotted. Not available if netcox_obj is a netcox fit.
type	Graphical argument to be passed to matplot, a character string (length 1 vector) or vector of 1-character strings indicating the type of plot for each column of y, see plot.default for all possible types. Default is "l" for lines.
log	Graphical argument to be passed to matplot, a character string which contains "x" if the x axis is to be logarithmic, "y" if the y axis is to be logarithmic, "" if neither, "xy" or "yx" if both axes are to be logarithmic. Default is "x".
...	Further arguments of matplot and ultimately of plot.default for some.

Value

Produces a coefficient profile plot of the coefficient paths for a fitted netcox or netcox_cv object.

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)
# plot solution path from a netcox fit
fit <- netcox(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,
              tol = 1e-4,
              maxit = 1e3,
              verbose = FALSE)
plot_netcox_sp(netcox_obj = fit)
              
# plot solution path from a netcox_cv fit              
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_sp(netcox_obj = cv, plot_min = TRUE, plot_1se = TRUE)               

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