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The data consist of measures of yield of a chemical manufacturing process for acetylene in relation to numeric parameters.

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)

Source

SAS documentation example for PROC REG, Ridge Regression for Acetylene Data.

Details

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.

Typical models for these data include the interaction of temp:ratio, and a squared term in temp

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)