Description of the program: nstep


This program makes depending on whether -0 is set either a local linear ansatz or a zeroth order ansatz for a possibly multivariate time series and iterates a artificial trajectory. The initial values for the trajectory are the last points of the original time series. Thus it actually forecasts the time series.

Usage:

nstep [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 points to use whole file
-x# number of lines to be ignored 0
-m# # of components,embedding dimension 1,2
-c# columns to be read 1,...,# of components
-d# delay for the embedding 1
-L# length of prediction 1000
-k# minimal numbers of neighbors for the fit 30
-r# neighborhood size to start with (interval of data)/1000
-f# factor to increase the neighborhood size
if not enough neighbors were found
1.2
-0 perform a zeroth order fit instead of a local linear one not set (local linear)
-o[#] output file name without name: 'datafile'.cast
(or stdin.cast if data were read from stdin)
without -o results are written to stdout
-V# verbosity level
  0: only panic messages
  1: add input/output messages
1
-h show these options none


Description of the Output

The output is just the components of the forecasted time series.
View the C-sources.
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