View source: R/model_performance.R
rmse | R Documentation |
Compute root mean squared error.
rmse(object, data)
object |
fitted model |
data |
data.frame (defaults to NULL) |
The RMSE is the square root of the average of squared differences between prediction and actual observation and indicates the absolute fit of the model to the data. It can be interpreted as the standard deviation of the unexplained variance, and is in the same units as the response variable. Lower values indicate better model fit.
numeric value
Martin Haringa
x <- glm(nclaims ~ area, offset = log(exposure), family = poisson(), data = MTPL2) rmse(x, MTPL2)
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