The Data Validation Tool requires both an observation data set as a baseline,
and a model to validate. In addition to validating model data, users can also
compare 2 observation stations.
Bias:
The bias (or bias function) of an estimator is the difference between the estimator's
expected value and the true value of the parameter being estimated.
RMS:
Root-mean-square error is a measure of the differences between model and observations.
Scatter Index:
Scatter index is calculated by dividing root-mean-square deviation with mean of the baseline observations.
It presents the RMS difference with respect to the mean baseline observations.
R2:
A statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination,
or the coefficient of multiple determination for multiple regression.
Circular Correlation:
For directional data, the circular correlation is a correlation coefficient to measure association between angular variables.
Num Points:
This is the number of points found in the analysis. The observation data is subsampled (if necessary) to match the model data in time.