Description of the program: false_nearest


This program looks for the nearest neighbors of all data points in m dimensions and iterates these neighbors one step into the future. If the ratio of the distance of the iteration and that of the nearest neighbor exceeds a given threshold the point is marked as a wrong neighbor. The output is the fraction of false neighbors for the specified embedding dimensions (see Kennel et al.).

Note: We implemented a new second criterion. If the distance to the nearest neighbor becomes smaller than the standard deviation of the data devided by the threshold, the point is omitted. This turns out to be a stricter criterion, but can show the effect that for increasing embedding dimensions the number of points which enter the statistics is so small, that the whole statistics is meanlingless. Be aware of this!


Usage:

false_nearest [Options]

Everything not being a valid option will be interpreted as a potential datafile name. Given no datafile at all, means read stdin. Also - means stdin

Possible options are:

Option Description Default
-l# number of data to use whole file
-x# ignore the first # rows 0
-c# column to be read 1
-m# minimal dimension of the delay vectors 1
-M# maximal dimension of the delay vectors 5
-d# delay of the vectors 1
-f# ratio factor 10.0
-t# theiler window 0
-o[#] output file name without file name: 'datafile'.fnn
(or stdin.del if stdin was read)
If no -o is given stdout is used
-V# verbosity level
  0: only panic messages
  1: add input/output messages
  2: add information about the current state of the program
3
-h show these options none


Description of the Output:

output on stdout (or in the file):
first column: the embedding dimension
second column: the fraction of false nearest neighbors
third column: the average size of the neighborhood
fourth column: the average of the squared size of the neighborhood
output on stderr:
A statistics on how many points were found up to the given neighborhood size.
View the C source.
Table of Contents * TISEAN home