Pottery2: Chemical Analysis of Romano-British Pottery
In heplots: Visualizing Hypothesis Tests in Multivariate Linear Models

Description Usage Format Details Source References See Also Examples

Results of chemical analyses of 48 specimens of Romano-British pottery published by Tubb et al. (1980). The numbers are the percentage of various metal oxides found in each sample for elements of concentrations greater than 0.01%. This is the original data set from Tubb et al. (1980), in contrast to Pottery.

1	data(Pottery2)

A data frame with 48 observations on the following 12 variables.

Region: a factor with levels Gl NF Wales
Site: a factor with levels AshleyRails Caldicot Gloucester IsleThorns Llanedryn
Kiln: a factor with levels 1 2 3 4 5
Al: amount of aluminum oxide, Al_2O_3
Fe: amount of iron oxide, Fe_2O_3
Mg: amount of magnesium oxide, MgO
Ca: amount of calcium oxide, CaO
Na: amount of sodium oxide, Na_2O
K: amount of potassium oxide, K_2O
Ti: amount of titanium oxide, TiO_2
Mn: amount of manganese oxide, MnO
Ba: amount of BaO

The specimens are identified by their rownames in the data frame. Kiln indicates at which kiln site the pottery was found; Site gives the location names of those sites. The kiln sites come from three Regions, ("Gl"=1, "Wales"=(2, 3), "NF"=(4, 5)), where the full names are "Gloucester", "Wales", and "New Forrest".

The variable Kiln comes pre-supplied with contrasts to test interesting hypotheses related to Site and Region.

Slightly modified from files found at: http://people.tamu.edu/~dcarlson/quant/data/RBPottery.html

Baxter, M. J. 2003. Statistics in Archaeology. Arnold, London.

Tubb, A., A. J. Parker, and G. Nickless. 1980. The Analysis of Romano-British Pottery by Atomic Absorption Spectrophotometry. Archaeometry, 22, 153-171.

Pottery for the related (subset) data set

data(Pottery2)
# contrasts for Kiln correspond to between Region [,1:2] and within Region [,3:4]
contrasts(Pottery2$Kiln)

pmod <-lm(cbind(Al,Fe,Mg,Ca,Na,K,Ti,Mn,Ba)~Kiln, data=Pottery2)
Anova(pmod)

# extract coefficient names for linearHypotheses
coefs <- rownames(coef(pmod))[-1]

# test differences among regions
linearHypothesis(pmod, coefs[1:2])
# test differences within regions B, C
linearHypothesis(pmod, coefs[3:4])

heplot(pmod, fill=c(TRUE,FALSE), hypotheses=list("Region" =coefs[1:2], "WithinBC"=coefs[3:4]))

# all pairwise views;  note that Ba shows no effect
pairs(pmod, fill=c(TRUE,FALSE))

# canonical view, via candisc::heplot

if (require(candisc)) {

# canonical analysis: how many dimensions?
(pcan <- candisc(pmod))

heplot(pcan, scale=18, fill=c(TRUE,FALSE), var.col="darkgreen", var.lwd=2, var.cex=1.5)

## Not run: 
heplot3d(pcan, scale=8)

## End(Not run)
}