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 | 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). | ||
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: | ||
==== | ====Input and Output Cases==== | ||
* '''Case A):''' '''y1''' is a matrix or vector | * '''Case A):''' '''y1''' is a matrix or vector |
Revision as of 10:00, 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 measured 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.