Figure 1. Plot of Blue MCDs by Dimension 1 scores for 50 shovel-test-pit assemblages from the Mona Great House.

Figure 2. Plot of ware types from the Mona Great House site 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 great house compounds, in the Caribbean through the use of shovel-test-pit surveys. For sites with extensive and standardized STP coverage, including the Mona Great House 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-Bayesian 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 Blue MCDs by Dimension 1 scores for 50 phased shovel-test-pit assemblages from the Mona Great House.

Figure 4. Plot of phased STPs from the Mona Great House by STP northing and easting.

Bayesian smoothing and CA analysis can be used on STP data from the Mona Great House site. The CA for the Mona Great House resulted in two phases for the site.  The nearly identical dates for the two phases suggests that the CA, while capturing a mild temporal trend, likely represents social differences between the Great House and the surrounding dependencies.  Phase 1 and Phase 2 have MCDs of 1763 and 1768 respectively.  Two other measures, TPQp90 and TPQp95, are less sensitive to excavation errors and taphonomic processes that might introduce a small amount of anomalously late material into an assemblage were used to refine the analysis. The TPQp90 provides a more robust estimate of the site's TPQ based on the 90th percentile of the beginning manufacturing dates for all the artifacts comprising it. TPQp95 provides a robust estimate of the site's TPQ based on the 95th percentile of the beginning manufacturing dates for all the artifacts comprising it. The TPQp95s of 1763 for Phase I and 1762 for Phase 2and suggest that Phase 1 and Phase 2 date from virtually the same time period. TPQp95s of 1763 for Phase 1 and 1762 for Phase 2 suggest that Phase 1 and Phase 2 date from virtually the same time period.

The smoothed ceramic ware-type frequencies fit the expectations of the seriation model, witness the point configuration in the plot of STP assemblages on the first two CA dimensions (Figure 1). The corresponding plot of ware types along CA axis 1 reveals a slight temporal trend but  more strongly suggests social distance: high-style, costly imported wares such as Chinese Porcelain and Delft types are in Phase 1 (Figure 2, Figure 3). While Phase 2 also consists of expensive tablewares such as creamware and white salt glaze, this Phase is dominated by coarse earthenwares, many of which were of local manufacture.  When the Phase assignments were mapped onto the shovel-test-pits, there was a striking relationship between Phase 1 ceramics and the location of the great house and the location of Phase 2, where coarse earthenwares and slightly later tablewares spread a across the rest of the site, encompassing the flankers and likely other out buildings surrounding the Great House.  The location of Phase 2 STPs may also suggest that when the Great House was abandoned, likely sometime in the 1770s, enslaved laborers may have continued to occupy the outlying dependencies for a short period afterwards (Figure 4).