The data consist of measures of yield of a chemical manufacturing process
for acetylene in relation to numeric parameters.
Marquardt and Snee (1975) used these data to illustrate ridge regression
in a model containing quadratic and interaction terms,
particularly the need to center and standardize variables appearing in
high-order terms.
Usage
data(Acetylene)
Format
A data frame with 16 observations on the following 4 variables.
yield
conversion percentage yield of acetylene
temp
reactor temperature (celsius)
ratio
H2 to N-heptone ratio
time
contact time (sec)
Details
Typical models for these data include the interaction of temp:ratio,
and a squared term in temp
Source
SAS documentation example for PROC REG, Ridge Regression for Acetylene Data.
References
Marquardt, D.W., and Snee, R.D. (1975), "Ridge Regression in
Practice," The American Statistician, 29, 3-20.
Marquardt, D.W. (1980),
"A Critique of Some Ridge Regression Methods: Comment,"
Journal of the American Statistical Association,
Vol. 75, No. 369 (Mar., 1980), pp. 87-91
Examples
data(Acetylene)
# naive model, not using centering
amod0 <- lm(yield ~ temp + ratio + time + I(time^2) + temp:time, data=Acetylene)
y <- Acetylene[,"yield"]
X0 <- model.matrix(amod0)[,-1]
lambda <- c(0, 0.0005, 0.001, 0.002, 0.005, 0.01)
aridge0 <- ridge(y, X0, lambda=lambda)
traceplot(aridge0)
traceplot(aridge0, X="df")
pairs(aridge0, radius=0.2)