pmlogreg: Piecewise monotone logistic regression with taut strings

Description Usage Arguments Value Author(s) See Also Examples

Description

Applies the taut string method to binary data.

Usage

1
2
pmlogreg(y, thr.const=2.5, verbose=FALSE, extrema.nr=-1, bandwidth=-1, 
localsqueezing=TRUE, squeezing.factor=0.5, tolerance=0.001,extrema.mean=TRUE)

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

extrema.nr

if set to a positive integer an approximation with the specified number of local extreme values is calculated

bandwidth

if set to a positive value the specified bandwidth is used instead of the multiresolution criterion.

localsqueezing

logical, if T (default) the bandwidth is changed locally.

squeezing.factor

The amount of decrement applied to the bandwidthes

tolerance

Accuracy used for the determination of the bandwidth when extrema.nr is greater than 0.

extrema.mean

logical, if T (default) the value of the taut string approximation at local extreme values is set to the mean of the observations on the interval where the extremum is taken.

Value

A list with components

y

The approximation of the given data

widthes

Bandwidth used

nmax

Number of local extreme values

knotsind

Indices of knot points

knotsy

y-koordinates of knots of the taut string

Author(s)

Arne Kovac A.Kovac@bristol.ac.uk

See Also

l1pmreg,pmden,pmspec

Examples

1
2
aaa<-rbinom(1024,1,0.5+0.5*sin(seq(0,10*pi,len=1024)))
pmlogreg(aaa,verbose=TRUE)$n

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

Related to pmlogreg in ftnonpar...