### Simple nonlinear prediction

`predict -d# -m# [-r# | -v#] [-s# -o `*outfile*` -l# -x# -c# -V# -h] `* file(s)*

` -d `delay

` -m `embedding dimension

` -r `absolute radius of neighbourhoods

` -v `same as fraction of standard deviation

` -s `time steps ahead forecast (one step)

` -l `number of values to be read (all)

` -x `number of values to be skipped (0)

` -c `column to be read (1 or *file*,#)

` -o `output file name, just ` -o `means *file*`_pred`

` -V `verbosity level (0 = only fatal errors)

` -h `show this message

Performs locally constant predictions
on scalar time series and prints the
root mean squared prediction error.
Predictions are made a time ahead given by `-s`.
Either `-r`
or `-v` must be present.
Predictions are written to *file*_`pred`.
**Note:** A version of fclazy is used that implements
fast neighbour search (not like in the book).

See also zeroth which does essentially the
same but has some different options, including multivariate data, and
xzero, which does cross-predictions.

Table of Contents * TISEAN home