diagnostic.PLR {LorenzRegression} | R Documentation |
diagnostic.PLR
provides diagnostic information for an object of class "PLR"
It restricts the path of the PLR to pairs of parameters (grid, lambda) that satisfy a threshold criterion.
diagnostic.PLR(
object,
tol = 0.99,
method = c("union", "intersect", "BIC", "Boot", "CV")
)
object |
An object of class |
tol |
A numeric threshold value used to restrict the PLR path. More specifically, we restrict to pairs (grid,lambda) whose normalized score exceeds |
method |
A character string specifying the method used to evaluate the scores.
Options are
|
A list with two elements:
path
The restricted model path, containing only the values of the pair (grid, lambda) that satisfy the threshold criterion.
best
The best model. It is obtained by considering the pair (grid, lambda) in the restricted path that leads to the sparsest model. If several pairs yield the same level of sparsity, we consider the pair that maximizes the minimum score across all selection methods available.
# Continuing the Lorenz.boot(.) example:
# The out-of-bag score seems to remain relatively flat when lambda is small enough
plot(PLR_boot, type = "diagnostic")
# What is the best pair (grid,penalty) parameter that is close enough to the highest OOB score
diagnostic.PLR(PLR_boot, tol = 0.99, method = "Boot")
# We want the solution to be close to the best, for both the BIC and OOB scores.
diagnostic.PLR(PLR_boot, method = "intersect")