plot.sox {sox}

Solution path plot for sox()

Description

Plot the solution path generated by sox().

Usage

## S3 method for class 'sox'
plot(x, type = "l", log = "x", ...)

Arguments

x

Fitted sox model.

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 sox model.

See Also

sox, sox_cv.

Examples

x <- as.matrix(sim[, c("A1","A2","C1","C2","B","A1B","A2B","C1B","C2B")])
lam.seq <- exp(seq(log(1e0), log(1e-3), length.out = 20))

overlapping.groups <- list(c(1, 2, 6, 7),
                           c(5, 6, 7, 8, 9),
                           c(6, 7),
                           c(3, 4, 8, 9),
                           c(8, 9))
                           
pars.overlapping <- overlap_structure(overlapping.groups)

fit.overlapping <- sox(
  x = x,
  ID = sim$Id,
  time = sim$Start,
  time2 = sim$Stop,
  event = sim$Event,
  penalty = "overlapping",
  lambda = lam.seq,
  group = pars.overlapping$groups,
  group_variable = pars.overlapping$groups_var,
  penalty_weights = pars.overlapping$group_weights,
  tol = 1e-4,
  maxit = 1e3,
  verbose = FALSE
)

plot(fit.overlapping)
              
cv.overlapping <- sox_cv(
  x = x,
  ID = sim$Id,
  time = sim$Start,
  time2 = sim$Stop,
  event = sim$Event,
  penalty = "overlapping",
  lambda = lam.seq,
  group = pars.overlapping$groups,
  group_variable = pars.overlapping$groups_var,
  penalty_weights = pars.overlapping$group_weights,
  nfolds = 5,
  tol = 1e-4,
  maxit = 1e3,
  verbose = FALSE
)

plot(cv.overlapping$sox.fit)