Learn R Programming

MASS (version 7.3-51.6)

petrol: N. L. Prater's Petrol Refinery Data

Description

The yield of a petroleum refining process with four covariates. The crude oil appears to come from only 10 distinct samples.

These data were originally used by Prater (1956) to build an estimation equation for the yield of the refining process of crude oil to gasoline.

Usage

petrol

Arguments

Format

The variables are as follows

No

crude oil sample identification label. (Factor.)

SG

specific gravity, degrees API. (Constant within sample.)

VP

vapour pressure in pounds per square inch. (Constant within sample.)

V10

volatility of crude; ASTM 10% point. (Constant within sample.)

EP

desired volatility of gasoline. (The end point. Varies within sample.)

Y

yield as a percentage of crude.

References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

Examples

Run this code
# NOT RUN {
library(nlme)
Petrol <- petrol
Petrol[, 2:5] <- scale(as.matrix(Petrol[, 2:5]), scale = FALSE)
pet3.lme <- lme(Y ~ SG + VP + V10 + EP,
                random = ~ 1 | No, data = Petrol)
pet3.lme <- update(pet3.lme, method = "ML")
pet4.lme <- update(pet3.lme, fixed = Y ~ V10 + EP)
anova(pet4.lme, pet3.lme)
# }

Run the code above in your browser using DataLab