capushe-package | R Documentation |
This package includes functions for model selection via penalization. The model
selection criterion has the following form: \gamma_n (\hat{s}_m)+scoef\times\kappa\times pen_{shape}(m)
.
Two algorithms based on the slope heuristics are proposed to calibrate the
parameter \kappa
in the penalty: the data-driven slope estimation algorithm (DDSE)
and the dimension jump algorithm (Djump).
The data-driven slope estimation algorithm and the dimension jump algorithm are
respectively implemented into the DDSE
function and the Djump
function. Somes
classes are defined for the outputs of DDSE
and Djump
and a graphical display is
available for each one of these two classes. DDSE
and Djump
are both included in
the capushe
function which is the main function of the package.
Sylvain Arlot, Vincent Brault, Jean-Patrick Baudry, Cathy Maugis and Bertrand Michel.
Maintainer: Vincent Brault <vincent.brault@math.u-psud.fr>
http://www.math.univ-toulouse.fr/~maugis/CAPUSHE.html
http://www.math.u-psud.fr/~brault/capushe.html
Article: Baudry, J.-P., Maugis, C. and Michel, B. (2011) Slope heuristics: overview and implementation. Statistics and Computing, to appear. doi: 10.1007/ s11222-011-9236-1
Djump
and DDSE
for model selection
algorithms based on the slope heuristics. plot
for a
graphical display of the two algorithms. validation
to check that the slope heuristics can be applied confidently.
data(datacapushe)
## capushe returns the same model with DDSE and Djump:
capushe(datacapushe)
## capushe also returns the model selected by AIC and BIC
capushe(datacapushe,n=1000)
## Djump only
Djump(datacapushe)
## DDSE only
DDSE(datacapushe)
## Graphical representations
plot(Djump(datacapushe))
plot(DDSE(datacapushe))
plot(capushe(datacapushe))
## Validation procedure
data(datapartialcapushe)
capushepartial=capushe(datapartialcapushe)
plot(capushepartial)
## Additional data
data(datavalidcapushe)
validation(capushepartial,datavalidcapushe) ## The slope heuristics should not
## be applied for datapartialcapushe.
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