N. L. Prater's Petrol Refinery Data
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.
petrol
The variables are as follows
Nocrude oil sample identification label. (Factor.)
SGspecific gravity, degrees API. (Constant within sample.)
VPvapour pressure in pounds per square inch. (Constant within sample.)
V10volatility of crude; ASTM 10% point. (Constant within sample.)
EPdesired volatility of gasoline. (The end point. Varies within sample.)
Yyield as a percentage of crude.
N. H. Prater (1956) Estimate gasoline yields from crudes. Petroleum Refiner 35, 236–238.
This dataset is also given in D. J. Hand, F. Daly, K. McConway, D. Lunn and E. Ostrowski (eds) (1994) A Handbook of Small Data Sets. Chapman & Hall.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.