smdenreg {ftnonpar}R Documentation

Piecewise monotone density estimation with smooth taut strings

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 A.Kovac@bristol.ac.uk

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")

[Package ftnonpar version 0.1-83 Index]