FNN {fractal} | R Documentation |
Invokes the method of False Nearest Neighbors (FNN) to estimate the minimal embedding dimension of a multivariate data set.
FNN(x, dimension=5, tlag=NULL, rtol=10, atol=2, olag=1)
x |
a vector containing a uniformly-sampled real-valued time series. |
atol |
neighbor tolerance based on attractor size.
If the Euclidean distance between two neighbor candidates is
Atol times larger the estimated
"size" of the attractor, then those neighbors are declared as
false neighbors. Default: 2 . |
dimension |
the maximal embedding dimension. Default: 5 . |
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: 0 . |
rtol |
false neighbor Euclidean distance tolerance.
If the ratio of the Euclidean distances between neighbor candidates
in successive embedding dimensions exceeds Rtol ,
then those neighbors are declared as false neighbors. For example,
if Rtol=5 neighbor candidates that are separated
five times more so than in the previous embedding dimension are
declared false neighbors. Default: 10 . |
tlag |
the time delay between coordinates. Default: the decorrelation time of the autocorrelation function. |
an object of class FNN
.
"Embedding Dimension"
."FNN percentage"
....
par
function).print
function.
M. B. Kennel, R. Brown, and H. D. I. Abarbanel (1992), Determining embedding dimension for phase-space 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.
FNS
, embedSeries
, infoDim
, corrDim
, timeLag
, determinism
.
## perform False Nearest Neighbors tests on ## chaotic beam data for embedding dimensions 1 ## through 10, using a time delay embedding ## with a time lag of 10 and an orbital lag of ## 15 x <- FNN(beamchaos, tlag=10, olag=15 ) ## print the results print(x) ## plot the results plot(x)