steamUse | R Documentation |

The monthly use of steam (`Steam`

) in a factory may be
modeled and described as function of the
operating days per month (`Operating.Days`

) and
mean outside temperature per month (`Temperature`

).

data("steamUse", package="robustbase")

A data frame with 25 observations on the following 9 variables.

`Steam`

:regression response

*Y*, the poinds of steam used monthly.`fattyAcid`

:pounds of Real Fatty Acid in storage per month.

`glycerine`

:pounds of crude glycerine made.

`wind`

:average wind velocity in miles per hour (a numeric vector).

`days`

:an integer vector with number of days of that month, i.e., in

*28..31*.`op.days`

:the number of operating days for the given month (integer).

`freeze.d`

:the number of days below 32 degrees Fahrenheit (

*= 0*°C (C=Celsius)*=*freezing temperature of water).`temperature`

:a numeric vector of average outside temperature in Fahrenheit (F).

`startups`

:the number of startups (of production in that month).

Nor further information is given in Draper and Smith, about the place and exacts years of the measurements, though some educated guesses should be possible, see the examples.

Data from Draper and Smith, 1st ed, 1966; appendix A.

A version of this has been used in teaching at SfS ETH Zurich, since at least 1996, https://stat.ethz.ch/Teaching/Datasets/NDK/dsteam.dat

The package aprean3 contains all data sets from the 3rd
edition of Draper and Smith (1998), and this data set with variable
names `x1 .. x10`

(`x9`

being `wind^2`

, hence extraneous).

Draper and Smith (1981) Applied Regression Analysis (2nd ed., p. 615 ff)

## Not run: if(require("aprean3")) { # show how 'steamUse' is related to 'dsa01a' stm <- dsa01a names(stm) <- c("Steam", "fattyAcid", "glycerine", "wind", "days", "op.days", "freeze.d", "temperature", "wind.2", "startups") ## prove that wind.2 is wind^2, "traditionally" rounded to 1 digit: stopifnot(all.equal(floor(0.5 + 10*stm[,"wind"]^2)/10, stm[,"wind.2"], tol = 1e-14)) ## hence drop it steamUse <- stm[, names(stm) != "wind.2"] } ## End(Not run) data(steamUse) str(steamUse) ## Looking at this, cbind(M=rep_len(month.abb, 25), steamUse[,5:8, drop=FALSE]) ## one will conjecture that these were 25 months, Jan--Jan in a row, ## starting in a leap year (perhaps 1960 ?). plot(steamUse) summary(fm1 <- lmrob(Steam ~ temperature + op.days, data=steamUse)) ## diagnoses 2 outliers: month of July, maybe company-wide summer vacations ## KS2014 alone seems not robust enough: summary(fm.14 <- lmrob(Steam ~ temperature + op.days, data=steamUse, setting="KS2014")) pairs(Steam ~ temperature+op.days, steamUse)