Matlab
Programs
Total-variation regularized
logistic discrimination
Runs the regularized logistic discrimination of Rühlicke and
Gervini (2007). For the time being, for two groups only.
Download: TVLogDis.m
Choosing PCs
This function computes the d-plot for selection of significant
principal components. See Auer and Gervini (2006).
Download: dplot.m
Free-knot
splines for
functional data
Here are the Matlab functions
used in Gervini (2006).
FKSMEAN and FKSPC compute, respectively, free-knot spline estimates of
the mean function and the principal components of a sample of
univariate curves. Related subroutines are also given.
Download: fksmean.m
, fkspc.m
, spfpc.m ,
bspl.m
and jupp.m
Nonparametric
MLE of structural mean
and warping functions
This is the estimator
introduced in Gervini & Gasser (2005).
MLREG computes the nonparametric MLE of the mean and related stuff
(warping functions, registered curves,
individual predictors of the parameters). BOOTMLREG bootstraps the
estimator and is used to construct confidence bands.
Download: mlreg.m
, bootmlreg.m
Self-modeling registration
Routine SMREG carries out
self-modeling registration of functional
data, as introduced in Gervini & Gasser (2004). The fast
cross-validation procedure to select the number of components is
implemented in FASTCV. Additionally, you need to download BSPL, which
computes B-spline basis functions and their derivatives, and ISOTONE,
which computes isotonic regression (I took this one from Jim Ramsay's
package).
Download: smreg.m
, fastcv.m
, bspl.m and
isotone.m
Landmark registration and
identification
Routine LANDREG performs
(univariate) landmark registration. The curves
are assumed to be sampled on a common time grid, although missing
values
are acceptable (missing landmarks are acceptable too).
For a quick-and-dirty graphical identification of landmarks, use LANDID.
Download: landreg.m
, landid.m
REWLS estimator
Program REWLS computes the reweighted regression estimator of Gervini
& Yohai (2002). As initial estimator I recommend the use of a
high-breakdown S-estimator (computed by SREG) or alternatively the
Least Median of Squares estimator (computed by LMSREG).
Download: rewls.m
, sreg.m , lmsreg.m
|