msdr
msdr
Calculates the Mean squared deviation ratio (msdr) from observed and predicted values.
Usage
msdr(o, p)Arguments
- o
A numeric vector. Observed values.
- p
A numeric vector. Predicted values.
Details
Interpretation: closer to 1 is better. Sometimes called standardised squared predictor error (SSPE) or scaled root mean squared error (SRMSE).
Value
Mean squared deviation ratio (msdr)
References
Piikki K., Wetterlind J., Soderstrom M., Stenberg B. (2021). Perspectives on validation in digital soil mapping of continuous attributes. A review. Soil Use and Management. 10.1111/sum.12694
Voltz, M., & Webster, R. (1990). A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. Journal of soil Science, 41(3), 473-490. (there called: standardized square deviation).
Examples
# NOT RUN {
obs<-c(1:10)
pred<-c(1, 1 ,3, 2, 4, 5, 6, 8, 7, 10)
msdr(o=obs, p=pred)
# }