Statistics: Difference between revisions
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*Root-Mean-Squared Error | *Root-Mean-Squared Error | ||
{{Equation|<math> RMSE = \sqrt{ \bigg\langle \big( x_m - x_c \big)^2 \bigg\rangle } </math>|2=2}} | {{Equation|<math> RMSE = \sqrt{ \bigg\langle \big( x_m - x_c \big)^2 \bigg\rangle } </math>|2=2}} | ||
*Normalized-Root-Mean-Squared Error | *Normalized-Root-Mean-Squared Error | ||
{{Equation|<math> RRMSE = \frac{\sqrt{ \bigg\langle \big( x_m - x_c \big)^2 \bigg\rangle}}{range(x_m)} </math>|2=2}} | {{Equation|<math> RRMSE = \frac{\sqrt{ \bigg\langle \big( x_m - x_c \big)^2 \bigg\rangle}}{\text{range}(x_m)} </math>|2=2}} | ||
*Mean-Absolute Error | *Mean-Absolute Error | ||
{{Equation|<math> MAE = \bigg\langle \big| x_m - x_c \big| \bigg\rangle </math>|2=5}} | {{Equation|<math> MAE = \bigg\langle \big| x_m - x_c \big| \bigg\rangle </math>|2=5}} | ||
*Normalized-Mean-Absolute Error | *Normalized-Mean-Absolute Error |
Revision as of 17:45, 1 June 2011
Given the initial measured values , final observed or measured values and final calculated values , there are several goodness of fit statistics or skill scores which can be calculated. The definition for some of the more common ones are provided below.
- Brier Skill Score
(1) |
- Root-Mean-Squared Error
(2) |
- Normalized-Root-Mean-Squared Error
(2) |
- Mean-Absolute Error
(5) |
- Normalized-Mean-Absolute Error
(5) |
- Correlation coefficient is defined as
(7) |
The bias is given by
(8) |