https://github.com/cran/pracma
Raw File
Tip revision: c79a04b5074656b36e591191eb8137b70a349932 authored by Hans W. Borchers on 30 June 2014, 00:00:00 UTC
version 1.7.0
Tip revision: c79a04b
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 }
back to top