smdenreg: Piecewise monotone density estimation with smooth taut...

In ftnonpar: Features and Strings for Nonparametric Regression

Description

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

Usage

smdenreg(x, verbose = FALSE, bandwidth=-1, maxkuipnr=19,asympbounds=FALSE, 
squeezing.factor=0.9, firstlambda=10,smqeps=1/length(x),fsign=double(0),
gensign=TRUE,...)

Arguments

x	observed values
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 automatic criterion based on generalized Kuiper metrics.
maxkuipnr	The order of the highest generalized Kuiper metric used for the automatic choice of the bandwidth
asympbounds	If set to T asymptotic bounds derived from a Brownian Bridge are used for the Kuiper criterion. Otherwise simulated bounds for various sample sizes are interpolated for the size of the data x
squeezing.factor	The amount of decrement applied to the bandwidthes
firstlambda	Initial value of lambda's for 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.
...	Passed to the plot command if verbose=T.

Value

x	The sorted data
y	values of the density approximation between the observations
nmax	Number of local extreme values
trans	taut string at the observations, should look like uniform noise

Author(s)

Arne Kovac [e-mail]

References

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

See Also

pmreg,l1pmreg,pmspec

Examples

y <- rclaw(500)
hist(y,col="lightgrey",40,freq=FALSE)
lines(smdenreg(y),col="red")

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