Montgomery and Peck (1982) illustrated variable selection techniques on the Hald cement data and gave several references to other analysis. The response variable *y* is the *heat evolved* in a cement mix. The four explanatory variables are ingredients of the mix, i.e., x1: *tricalcium aluminate*, x2: *tricalcium silicate*, x3: *tetracalcium alumino ferrite*, x4: *dicalcium silicate*. An important feature of these data is that the variables x1 and x3 are highly correlated (corr(x1,x3)=-0.824), as well as the variables x2 and x4 (with corr(x2,x4)=-0.975). Thus we should expect any subset of (x1,x2,x3,x4) that includes one variable from highly correlated pair to do as any subset that also includes the other member.

1 |

`hald`

is a matrix with 13 observations (rows) and 5 variables (columns), the first column is the dependent variable. `y.hald`

and `x.hald`

are also availables.

Montgomery, D.C., Peck, E.A. (1982)
*Introduction to linear regression analysis,*
John Wiley, New York.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.