Figure 1. Plot of Blue MCDS by Dimension 1 scores for 95 phased shovel-test-pit assemblages from the Mona Village.

Figure 2. Plot of ware types from Mona Village along CA Dimension 1 and 2. Note early types on the right, late ones of the left.

DAACS staff aims to produce a seriation-based chronology for each site using the same methods (see Neiman, Galle, and Wheeler 2003 for technical details). The majority of sites in the archive are comprised of data derived from deposits within quadrats. On these sites, only assemblages from features or stratigraphic groups with more than five ceramic sherds are included in these ceramic-based seriations. Plowzone contexts do not contribute to a DAACS seriation-based chronology.

The DAACS Caribbean Initiative focuses on exploring large-scale change on slave villages, or areas of where enslaved individuals lived and labored, such as a great house compound, in the Caribbean through the use of shovel-test-pit surveys. For sites with extensive and standardized STP coverage, including the Mona Village site, a variation on our site-based seriation method is employed. This is because each STP is small (50 cm. in diameter) and provides a small artifact sample. As a result, STP assemblages are rife with sampling error. The samples from individual STPs are so small that variation among STPs is almost entirely statistical noise.

Successfully analyzing STP data, without first aggregating those pits into counting units called sites, requires methods to suppress sampling error. Here we use empirical-Bayes methods. They offer a smart way to smooth both artifact density surfaces and relative frequencies of artifact types. To understand how these methods work, consider an STP - let's call it STP 12. The number of artifacts found in STP 12 is likely to be similar to the number of artifacts in the STPs within a certain distance of it. The information contained in the neighborhood of pits is combined with the actual number of artifacts from STP 12 to arrive at an estimate of artifact counts that are less influenced by sampling error (Neiman et al. 2008).

We use two forms of Bayesian smoothing in succession. First, to smooth counts of ceramic ware types in individual STPs, we use a gamma-Poisson model. The gamma-Poisson algorithm smoothes counts of individual artifact types in each STP, based on the counts for that type in nearby STPs. We then use a beta-binomial model to estimate relative frequencies (percentages or proportions) of ceramic ware types in individual STPs. Together two forms of Bayesian smoothing provide smoothed, stable estimates of artifact-type frequency variation in individual STPs, allowing us to see overall site patterning that may otherwise be distorted using raw data (Neiman et al. 2008).

To infer a chronology from the STPs we used correspondence analysis (CA) of ware-type frequencies. We employ CA because with the numbers of STP assemblages in the hundreds, a traditional manual frequency seriation is completely impractical. CA converts a data matrix of ware-type frequencies into a set of scores which estimate the positions of the assemblages on underlying axes or dimension of variation. MCDs are weighted averages of the historically documented manufacturing date for each ware type found in an assemblage, where the weights are the relative frequencies of the types. Measuring the correlation between CA axis scores and MCDs offer an indication of whether the CA scores capture time (Ramenofsky, Neiman and Pierce 2009).

Figure 3. Plot of Phased STPs from the Mona Village by STP northing and easting.

Bayseian smoothing and CA analysis can be used on STP data from the Mona Village site. The CA for the Mona Village resulted in three occupational phases for the survey area.  What remains of the Mona Village date from the 1770s through the 1820s.  With much of the village area destroyed by construction in the 1960s, it is likely that an even later occupation of the village lies to the north of the survey area under the Natural Sciences Complex. The MCDs and TPQs suggest that the portion of the village captured in the survey was occupied first along the eastern edge of the survey area, closest to the Mona Works. As the village grew in size, the data suggest that it spread toward the west and we can only assume north as well. 

The smoothed ceramic ware-type frequencies for the village fit the expectations of the seriation model well, witness the point configuration in the plot of STP assemblages on the first two CA dimensions (Figure 1). The corresponding plot of ware types reveals that CA axis 1 reflects a slight temporal trend with Nottingham, White Salt Glaze stoneware, and Whieldon Wares representing Phase 1 on the right and Pearlware, Yellow Ware, and unidentifiable but likely locally-produced coarse earthenware on the left, representing Phase 3 (Figure 2).  Phase 2 ceramics include Delft, Chinese Porcelain, and Afro-Caribbean Ceramics. When the phase assignments were mapped onto the shovel-test-pits, the earliest, Phase 1 occupation is seen along the eastern side of the site, near Queen's Way, with Phase 2 and Phase 3 trending to the west (figure 3). The true spatial and temporal extent of the Mona village will never be completely known but the survey provides a glimpse of mid-18th to early-19th century occupation along the southern edges of the village.