steamUse | R Documentation |

## Steam Usage Data (Excerpt)

### Description

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`

).

### Usage

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

### Format

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).

### Details

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.

### Source

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).

### References

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

### Examples

```
## 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)
```