Navigation

Operators and Keywords

Function List:

C++ API

Function File: output = lzo_gm (S)
Function File: output = lzo_gm (S, paramName, paramValue, …)

Estimates the average forecast error for a local constant (zeroth order) fit as a function of the neighborhood size. The name "lzo_gm" means ’local zeroth order -> global mean’.

Input

S

This function always assumes that each time series is along the longer dimension of matrix S. It also assumes that every dimension (counting along the shorter dimension) of S is considered a component of the time series.

Parameters

m

The embedding dimension used. It is synonymous to the second part of flag ’-m’ from TISEAN. The first part of the TISEAN flag is omitted as all of the available components of S are analyzed [default = 1].

d

Delay used for the embedding [default = 1].

i

For how many points should the error be calculated [default = length (S)].

rlow

The neighborhood size to start with [default = 1e-3].

rhigh

The neighborhood size to end with [default = 1].

f

Factor to increase neighborhood size if not enough neighbors were found [default = 1.2].

s

Steps to be forecast x(n+s) = f(x(n)) [default = 1].

c

Width of causality window [default = value of parameter s]

Output

The output is alligned with the input. If the components of the input(S) were column vectors then the number of columns of the output is 4 + number of components of S. In this case the output will have the following values in each row:

  • Neighborhood size (units of data)
  • Relative forecast error ((forecast error)/(variance of data))
  • Relative forecast error for the individual components of the input, this will take as many columns as the input has
  • Fraction of points for which neighbors were found for this neighborhood size
  • Average number of neighbors found per point

See also: lzo_test, lzo_run.

Algorithms

The algorithms for this functions have been taken from the TISEAN package.

Package: tisean