srmse: Standardised Root Mean Squared Error
In luke-a-rogers/pbsedm: An R package to implement some of the methods of empirical dynamic modelling
srmse R Documentation
Standardised Root Mean Squared Error
Description
Standardised Root Mean Squared Error
Usage
srmse(x, y)
Arguments
x
[numeric()][vector()] observed values
y
[numeric()][vector()] forecast values
Value
[numeric()] root mean squared error
Examples
x <- rnorm(100, 0, 1)
y1 <- x
srmse(x, y1)
y2 <- rep(mean(x), length(x))
srmse(x, y2)
luke-a-rogers/pbsedm documentation built on June 3, 2024, 5:20 a.m.
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| srmse | R Documentation |
Standardised Root Mean Squared Error
Description
Standardised Root Mean Squared Error
Usage
srmse(x, y)
Arguments
x |
[numeric()][vector()] observed values |
y |
[numeric()][vector()] forecast values |
Value
[numeric()] root mean squared error
Examples
x <- rnorm(100, 0, 1)
y1 <- x
srmse(x, y1)
y2 <- rep(mean(x), length(x))
srmse(x, y2)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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