smqreg: Smooth piecewise monotone regression with taut strings

In ftnonpar: Features and Strings for Nonparametric Regression

Description

Applies the smooth taut string method to one-dimensional data.

Usage

smqreg(y, thr.const=2.5, verbose=FALSE, bandwidth=-1, 
sigma=-1, localsqueezing=TRUE, squeezing.factor=0.5, DYADIC=TRUE,
firstlambda=100,smqeps=1/length(y),fsign=double(0),gensign=TRUE,
tolerance = 1e-12,...)

Arguments

y	observed values (ordered by value of independent variable)
thr.const	smoothing parameter for the multiresolution criterion (should be approximately 2.5)
verbose	logical, if T progress (for each iteration) is illustrated grahically
bandwidth	if set to a positive value the specified bandwidth is used instead of the multiresolution criterion.
sigma	if set to a positive value sigma the standard deviation is set to sigma and not estimated from the data
localsqueezing	logical, if T (default) the bandwidth is changed locally.
squeezing.factor	The amount of decrement applied to the bandwidthes
DYADIC	If TRUE the multiresolution constraints are only checked on dyadic intervals.
firstlambda	Initial value of lambda's for local or global squeezing.
smqeps	Distance between the (equally-spaced) time points.
fsign	Monotonicity constraints, vector of size n-1 of -1,0 and 1's. If fsign[i]==1, then fhat[i+1]>= fhat[i]. If fsign[i]==-1, then fhat[i+1]<=f[i]. Otherwise no constraint at this position.
gensign	If TRUE the taut string method is used to automatically produce suitable monotonicity constraints.
tolerance	Precision for the nested intervals for solving the minimisation problem.
...	Passed to the plot command if verbose=T.

Value

A list with components

y	The approximation of the given data
nmax	Number of local extreme values
sigma	Standard deviation used

Author(s)

Arne Kovac [e-mail]

References

Kovac, A. (2006) Smooth functions and local extreme values. Technical Report

See Also

pmreg,mintvmon,l1pmreg,pmden,pmspec

Examples

data(djdata)
par(mfrow=c(2,2))
plot(djblocks,col="grey")
lines(smqreg(djblocks)$y,col="red")
plot(djbumps,col="grey")
lines(smqreg(djbumps)$y,col="red")
plot(djheavisine,col="grey")
lines(smqreg(djheavisine)$y,col="red")
plot(djdoppler,col="grey")
lines(smqreg(djdoppler)$y,col="red")

Example output

ftnonpar documentation built on May 2, 2019, 3:04 a.m.