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\name{welding}
\alias{welding}
\title{Data: Tensile Strength of Welds}
\description{
This is a highly fractionated two-level factorial design employed as a screening design
in an off-line welding experiment performed by the National Railway Corporation of Japan.
There were 16 runs and 9 experimental factors. The response variable is the observed
tensile strength of the weld, one of several quality characteristics measured. All other
variables are at plus and minus levels.
}
\usage{data(welding)}
\format{
A data frame containing the following variables.
All the explanatory variables are numeric with two levels, \code{-1} and \code{1}.
\tabular{lll}{
\tab \bold{Variable} \tab \bold{Description}\cr
\tab Rods \tab Kind of welding rods\cr
\tab Drying \tab Period of drying\cr
\tab Material \tab Welded material\cr
\tab Thickness \tab Thickness\cr
\tab Angle \tab Angle\cr
\tab Opening \tab Opening\cr
\tab Current \tab Current\cr
\tab Method \tab Welding method\cr
\tab Preheating \tab Preheating\cr
\tab Strength \tab Tensile strength of the weld in kg/mm. The response variable.\cr
}
}
\source{
\url{http://www.statsci.org/data/general/welding.html}
}
\references{
Smyth, G. K., Huele, F., and Verbyla, A. P. (2001). Exact and approximate REML for heteroscedastic regression. \emph{Statistical Modelling} \bold{1}, 161-175.
Smyth, G. K. (2002). An efficient algorithm for REML in heteroscedastic regression. \emph{Journal of Computational and Graphical Statistics} \bold{11}, 1-12.
}
\keyword{datasets}
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