# Description of the program: onestep

This program makes a local linear ansatz and estimates the one step prediction error of the model. It allows to determine the optimal set of parameters for the program nstep, which iterates the local linear model to get a clean trajectory. The given forecast error is normalized to the variance of the data.

## Usage:

onestep [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
-c# | column to be read | 1
-m# | embedding dimension | 2
-d# | delay for the embedding | 1
-n# | for how many points should the error be calculated | all
-k# | minimal numbers of neighbors for the fit | 30
-r# | neighborhood size to start with | (data interval)/1000
-f# | factor to increase the neighborhood size if not enough neighbors were found | 1.2
-s# | steps to be forecasted (x_{n+steps}=f(\vec{x}_n)) | 1
-V# | verbosity level 0: only panic messages 1: add input/output messages | 1
-h | show these options | none

## Description of the Output:

The output consists of one number only, the relative forecast error. Relative means, the forecast error is devided by the standard deviation of the data.

View the C-sources.

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