\name{H_ethanol}
\alias{ethanol}
\docType{data}
\title{ Engine exhaust fumes from burning ethanol }

\description{
  Ethanol fuel was burned in a single-cylinder engine.  For various
  settings of the engine compression and equivalence ratio, the
  emissions of nitrogen oxides were recorded.
}

\usage{ethanol}

\format{
  A data frame with 88 observations on the following 3 variables.
  \describe{
    \item{NOx}{Concentration of nitrogen oxides (NO and NO2) in
      micrograms/J.}
    \item{C}{Compression ratio of the engine.}
    \item{E}{Equivalence ratio--a measure of the richness of the air and
      ethanol fuel mixture.}
  }
}

\source{
  Brinkman, N.D. (1981) Ethanol Fuel---A Single-Cylinder Engine Study of
  Efficiency and Exhaust Emissions. \emph{SAE transactions},
  \bold{90}, 1410--1424.
}

\author{
  Documentation contributed by Kevin Wright.
}

\references{
  Cleveland, William S. (1993). \emph{Visualizing Data}.  Hobart Press,
  Summit, New Jersey.
}

\examples{
## Constructing panel functions on the fly
EE <- equal.count(ethanol$E, number=9, overlap=1/4)
xyplot(NOx ~ C | EE, data = ethanol,
       prepanel = function(x, y) prepanel.loess(x, y, span = 1),
       xlab = "Compression ratio", ylab = "NOx (micrograms/J)",
       panel = function(x, y) {
           panel.grid(h=-1, v= 2)
           panel.xyplot(x, y)
           panel.loess(x,y, span=1)
       },
       aspect = "xy")

# Wireframe loess surface fit.  See Figure 4.61 from Cleveland.
require(stats)
with(ethanol, {
  eth.lo <- loess(NOx ~ C * E, span = 1/3, parametric = "C", 
                  drop.square = "C", family="symmetric")
  eth.marginal <- list(C = seq(min(C), max(C), length.out = 25), 
                       E = seq(min(E), max(E), length.out = 25))
  eth.grid <- expand.grid(eth.marginal)
  eth.fit <- predict(eth.lo, eth.grid)
  wireframe(eth.fit ~ eth.grid$C * eth.grid$E,
            shade=TRUE,
	    screen = list(z = 40, x = -60, y=0),
	    distance = .1,
	    xlab = "C", ylab = "E", zlab = "NOx")
})
}

\keyword{datasets}