On this R-data statistics page, you will find information about the ethanol data set which pertains to Engine exhaust fumes from burning ethanol . The ethanol data set is found in the lattice R package. You can load the ethanol data set in R by issuing the following command at the console data("ethanol"). This will load the data into a variable called ethanol. If R says the ethanol data set is not found, you can try installing the package by issuing this command install.packages("lattice") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the ethanol R data set. The size of this file is about 1,315 bytes.

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.

NOx

Concentration of nitrogen oxides (NO and NO2) in micrograms/J.

C

Compression ratio of the engine.

E

Equivalence ratio–a measure of the richness of the air and ethanol fuel mixture.

Author(s)

Documentation contributed by Kevin Wright.

Source

Brinkman, N.D. (1981) Ethanol Fuel—A Single-Cylinder Engine Study of Efficiency and Exhaust Emissions. SAE transactions, 90, 1410–1424.

References

Cleveland, William S. (1993) 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")
})

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Dataset imported from https://www.r-project.org.