rmse
Description
rmse (Root-Mean-Square-Error) function, also called RMSD (Root-Mean-Square-Deviation) calculates the norm of the difference between a pair of datasets, and then the mean of the difference, and returns the square root of the mean.
The RMSE value between a prediction dataset y of n values /math-3a0e244132c36c88b17e1f6d1a395d6a.png "\{x_1, \ x_2,..., \ x_n\}")
and an observation dataset x /math-3b0946722de35e12b5a87e34d0bf6202.png "\{y_1, \ y_2,..., \ y_n\}")
, is given by:
/math-12e8ffc60eef5502a7705772c9b8d426.png "RMSE = \sqrt{\frac{\sum_{i=1}^{n} (y_i-x_i)^2}{n}}")
Syntax
double rmse(dataset vobs, dataset vpred)
Parameters
vobs
- Input, obsevation vector.
vpred
- Input, prediction vector.
Return
Return the root mean square error of vector vobs and vpred.
Note: Missing data, masked data and text in vobs and vpred won't be counted.
Example
//Calculate the root mean square error of column A and B. yr = rmse(col(A),col(B));