Description of the program: lyap_spec
This program estimates the whole spectrum of Lyapunov exponents for a
given, possibly multivariate, time series. Whole spectrum means: If d
components are given and the embedding
dimension is m than m*d exponents will be determined. The method is
based on the work of Sano and Sawada.
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:
||number of points to use
||number of lines to be ignored
||column to be read
||no. of components, embedding dimension
||minimal neighborhood size
||factor to increase the size of the neighborhood|
if not enough neighbors were found
||number of neighbors to use (this version uses exactly the number|
of neighbors specified. If found more, only the # nearest will be
||number of iterations
||number of points
||invert the order of the time series.|
Is supposed to help finding spurious exponents.
||output file name
(or stdin.lyaps if data were read from stdin)
if no -o is given stdout is used
0: only panic messages
1: add input/output messages
||show these options
Description of the Output:
The output consists of d*m+1 columns. The first
one shows the actual iteration, the next d*m
ones the estimates of the Lyapunov exponents in decreasing order. The
last lines show the average forecast error(s) of the local linear
model, the average neighborhood size used for fitting the model and
the last one the estimated Kaplan-Yorke dimension.
Output is written every 10 seconds (real time), approximately.
Remark on the delay embedding
In older versions of this program it was possible to change the delay
of the embedding. This option was removed for the reason that the way
the program handled this delay was not very efficient. Instead of
rewriting everything, we decided to completely remove this option. In
case you want to use delays other than 1, use the program delay to create a multivariate time series with
the desired delay and read this multivariate time series into lyap_spec.
View the C-sources.
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