Rmse: Difference between revisions

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===Description===
===Description===


RMSE is used to calculate the root mean square difference between two vectors or matrices. If the vectors or matrices contain matching model-estimated and measured quantities, then the output is the Root Mean Square Error (RMSE).
RMSE is used to calculate the root mean square difference between two vectors or matrices. If the vectors or matrices contain matching model-estimated and known quantities, then the output is the Root Mean Square Error (RMSE).


The output '''err''' depends on the input, and there are 3 possible cases, outlined below:
The output '''err''' depends on the input, and there are 3 possible cases, outlined below:

Revision as of 10:01, 9 October 2008

Purpose

Calculate Root Mean Square Difference (Error).

Synopsis

err = rmse(y1,y2)

Description

RMSE is used to calculate the root mean square difference between two vectors or matrices. If the vectors or matrices contain matching model-estimated and known quantities, then the output is the Root Mean Square Error (RMSE).

The output err depends on the input, and there are 3 possible cases, outlined below:

Input and Output Cases

  • Case A): y1 is a matrix or vector
err = rmse(y1);
The output err is the root mean square of the elements of y1.
  • Case B): y1 is a matrix or vector, y2 is the same size as y1
err = rmse(y1,y2);
The output err is the root mean square of the difference between y1 and y2.
  • Case C): y1 is a matrix or vector, y2 is a column vector
err = rmse(y1,y2);
The output err is the root mean square of the difference between each column of y1 and y2.
Example: For example, y2 is a reference and the rmse is calculated between each column of y1 and the vector y2.

See Also

crossval