### Simple nonlinear prediction

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

> `-d` delay
> `-m` embedding dimension (at least 2)
> `-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. The program mzeroth can handle multivariate data, and xzero does cross-predictions.

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