pmspec: Piecewise monotone spectral density approximation with taut...
In ftnonpar: Features and Strings for Nonparametric Regression

Description Usage Arguments Value Author(s) References See Also

Applies the taut string method to spectral densities.

1	pmspec(x, pks=0, alpha=0.9, sqzf=0.9, mult=0, lcl=0, ln=0, fig = 0, pow=10^-2)

`x`	data
`pks`	if pks=0 then the number of peaks is determined automatically. If pks = k >0 then a density with n paeks is returned `pks`
`alpha`	If pks=0 then on Gaussian test beds the number of peaks of the true density is at least the returned value with an asymptotic probability of at least alpha. If pks > 0 then the parameter is not operational `alpha`
`sqzf`	Squeeze factor for the taut string `sqzf`
`mult`	If mult = T then rescaled empirical density is compared with the exponential distribution only on intervals forming a multiresolution scheme. If T = F then all intervals are used. If the sample size of the data is less than 512 then T = F is default `mult`
`lcl`	If lcl = T then string is calculated using local squeezing. If lcl = F then global squeezing is used.`lcl`
`fig`	If fig = T then the data are automticall plotted `fig`
`ln`	If fig = T and ln = T then the densities are plotted on a log scale. If ln = F then no transformation is performed `ln`
`pow`	Peaks with a power less than pow * total power will be ignored

`edf`	Emprical spectral density
`df`	String density
`pks`	Number of peaks
`ll`	Lower boundary for string
`uu`	Upper boundary for string
`str`	String

Laurie Davies Laurie.Davies@uni-essen.de

Davies, P.L. snd Kovac, A. (2001) Local extremes, runs, strings and multiresolution, Annals of Statistics 29 (1) 1-65. Davies, P. L. and Kovac, A. (2002) Densities, Spectral Densities and Modality

pmreg,l1pmreg,pmden

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