Durbin watson
From Eigenvector Documentation Wiki
Contents |
Purpose
Criterion for measure of continuity.
Synopsis
- y = durbin_watson(x)
Description
The Durbin Watson criteria for the columns of x are calculated as the ratio of the sum of the first derivative of a vector to the sum of the vector itself. Low values means correlation in variables, high values indicates randomness. Input x is a column vector or array in which each column represents a vector of interest. Output y is a scalar or vector of Durbin Watson measures.
Inputs
- x: column vector or array where each column represents the vector of interest
Outputs
- y: scalar or vector of Durbin Watson measures