Description Usage Arguments Value Examples
This function selects the carx
model which minimizes the AIC among a set of carx
models
defined by a set of formulas or a list of regression formulas with a maximal AR order.
The model specification is supplied by formulas
which can be either a formula or a list of formulas.
For each formula, the function will estimate the carx
models with the AR order
from 1 to max.ar
inclusive.
If detect.outlier=TRUE
, outlier detection will be performed for each combination of model
formula and AR order.
The function returns a list
which consists of: 1) aicMat
which is a matrix of AIC
values where
each row contains the AICs of the model given by a specific regression formula with the AR order
ranging from 1 to mar.ar
(after incorporation of any found outlier if outlier detection if enabled), and
2) fitted
which is the fitted object of the selected model.
1 | carxSelect(formulas, max.ar, data = list(), detect.outlier = F, ...)
|
formulas |
a regression formula or a list of regression formulas. |
max.ar |
the maximal AR order. |
data |
a |
detect.outlier |
logical to specify whether outlier detection is performed (and incorporating in
the |
... |
other arguments to be supplied, if not null, it will be called with the selected model and data.
Examples include |
a carx
object with an additional element selectionInfo
which is a list consisting of the information about the selection, in particular,
aicMat
, the matrix of AIC where rows correspond to the model formulas and columns correspond to the AR orders.
1 2 3 4 5 6 7 8 9 | dataSim <- carxSimCenTS(nObs=100)
fmls <- list(M1=y~X1,M2=y~X1+X2,M3=y~X1+X2-1)
## Not run: cs = carxSelect(y~X1,max.ar=3,data=dataSim)
## Not run: cs = carxSelect(formulas=fmls,max.ar=3,data=dataSim)
## Not run:
#To compute confidence intervals for the selected model, call with CI.compute=TRUE.
cs = carxSelect(formulas=fmls,max.ar=3,data=dataSim,CI.compute=TRUE)
## End(Not run)
|
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