Filter and reconstruction of data analysed via spec.lomb
Description
Given an object of class lomb
, this function allows the
reconstruction of the input signal using (a) a frequency selection
of single or multiple frequency (ranges), and/or (b) the most
significant peaks in the periodogram.
Usage
1 2  filter.lomb(l = stop("No LombData"), newx = NULL, threshold = 6,
filt = NULL, phase = "nextnb")

Arguments
l 
lomb object 
newx 
vector of new values at which the restored function is to be evaluated 
threshold 
statistical threshold in terms of a standard deaviation of the amplidudes. It determines which frequencies are used. Lower values give more frequencies. 
filt 
vector or matix of frequencies (ranges) in which to select the frequencies 
phase 
set the method to determine the phase at a given frequency (moegliche werte???) 
Details
To properly reconstruct the signal out of the calculated
lomb
object, three different methods are available, which are
controlled by the filt
argument.
If
filt=NULL
, the most significant values in the (dense) spectrum are used.If
filt=c(f1, .., fn)
, the given frequencies are used. The corresponding phase is approximated.If
class(filt)=="matrix"
, each row of the 2 x n matrix defines a frequency range. With in each range the "significant" frequencies are selected for reconstruction.
Prior to the reconstruction the filter.lomb
function calculates the
most significant amplitudes and corresponding phases. As a measure to select
the "correct" frequencies, the threshold
argument can be adjusted.
The corresponding phases of the underlying sine/cosinewaves are estimated by
one of the four following methods.

phase=="nextnb"
... use the phase of the bin of nearest neighbour. 
phase=="lin"
... linear interpolation between the two closest bins. 
phase=="lockin"
... principle of lockin amplification, also known as quadraturedemodulation technique. 
phase=="fit"
... nonlinear least squares fit withstats::nls
Value
This function returns a list which contains the reconstruction according to the
lomb
object and newx
for the given data x
and y
. The returned
object contains the following:
x,y
reconstructed signal
f,A,phi
used parameters from the
lomb
objectp
corresponding significance values