Use this function to list the required items and information that should be saved and retrieved from the model set search process in search.? functions.
get.search.items(
model = TRUE,
type1 = FALSE,
type2 = FALSE,
bestK = 1,
all = FALSE,
inclusion = FALSE,
cdfs = numeric(0),
extremeMultiplier = 0,
mixture4 = FALSE
)A list with the given options.
If TRUE, some information about the models is saved.
If TRUE and implemented, extra information is saved. This can be the coefficients in the SUR search or predictions in the VARMA search.
If TRUE and implemented, extra information is saved. This is similar to type1. It is reserved for future updates.
The number of best items to be saved in model, type1, or type2 information.
If TRUE, all models' information is saved.
If TRUE, inclusion weights are saved.
Weighted average of the CDFs at each given point is calculated (for type1 and type2 cases).
A number that determines the multiplier in the extreme bound analysis (for type1 and type2 cases). Use zero to disable it.
If TRUE, the first four moments of the average distributions are calculated in type1 and type2 cases.