Revision 04bbc417cf2927b827660bc07743429783569aec authored by HwB on 10 February 2013, 00:00:00 UTC, committed by Gabor Csardi on 10 February 2013, 00:00:00 UTC
1 parent 0e3ae6b
rmserr.Rd
\name{rmserr}
\alias{rmserr}
\title{
Accuracy Measures
}
\description{
Calculates different accuracy measures, most prominently RMSE.
}
\usage{
rmserr(x, y, summary = FALSE)
}
\arguments{
\item{x, y}{two vectors of real numbers}
\item{summary}{logical; should a summary be printed to the screen?}
}
\details{
Calculates six different measures of accuracy for two given vectors or
sequences of real numbers:
\tabular{ll}{
MAE \tab Mean Absolute Error\cr
MSE \tab Mean Squared Error\cr
RMSE \tab Root Mean Squared Error\cr
MAPE \tab Mean Absolute Percentage Error\cr
LMSE \tab Normalized Mean Squared Error\cr
rSTD \tab relative Standard Deviation
}
}
\value{
Returns a list with different accuracy measures.
}
\references{
Gentle, J. E. (2009). Computational Statistics, section 10.3.
Springer Science+Business Media LCC, New York.
}
\note{
Often used in Data Mining for \emph{predicting} the accuracy of predictions.
}
\examples{
x <- rep(1, 10)
y <- rnorm(10, 1, 0.1)
rmserr(x, y, summary = TRUE)
}
\keyword{ stat }
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