Estimation of the proper embedding dimension for a singlevariable time series
Description
Invokes the method of False Nearest Neighbors (FNN) to estimate the minimal embedding dimension of a multivariate data set.
Usage
1 
Arguments
x 
a vector containing a uniformlysampled realvalued time series. 
atol 
neighbor tolerance based on attractor size.
If the Euclidean distance between two neighbor candidates is

dimension 
the maximal embedding dimension. Default: 
olag 
orbital lag. The number of points along the
trajectory (orbit) of the current point
that must be exceeded in order for
another point in the phase space to be considered
a neighbor candidate. This argument is used
to help attenuate temporal correlation in the
the embedding which can lead to spuriously low
minimal embedding dimension estimates. The orbital lag
must be positive or zero. Default: 
rtol 
false neighbor Euclidean distance tolerance.
If the ratio of the Euclidean distances between neighbor candidates
in successive embedding dimensions exceeds 
tlag 
the time delay between coordinates. Default: the decorrelation time of the autocorrelation function. 
Value
an object of class FNN
.
S3 METHODS
 plot
plots a summary of the results. Available options are:
 xlab
a character string defining the xaxis label. Default:
"Embedding Dimension"
. ylab
a character string defining the yaxis label. Default:
"FNN percentage"
....
Additional plot arguments (set internally by the
par
function).
prints a summary of the results. Available options are:
 ...
Additional print arguments used by the standard
print
function.
References
M. B. Kennel, R. Brown, and H. D. I. Abarbanel (1992), Determining embedding dimension for phasespace reconstruction using a geometrical construction, Physical Review A, 45(6), 3403–3411.
Fredkin, D. R., and Rice, J. A. (1995), Method of false nearest neighbors: A cautionary note, Physical Review E, 51(4), 2950–2954.
See Also
FNS
, embedSeries
, infoDim
, corrDim
, timeLag
, determinism
.
Examples
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