Durbin watson: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Criterion for measure of continuity. | Criterion for measure of continuity. | ||
===Synopsis=== | ===Synopsis=== | ||
:y = durbin_watson(x) | :y = durbin_watson(x) | ||
===Description=== | ===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. | 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. | ||
===See Also=== | ===See Also=== | ||
[[coda_dw]] | [[coda_dw]] | ||
Revision as of 15:25, 3 September 2008
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.