A convenient and reproducible toolkit for relative and absolute dating
and analysis of chronological patterns. This package includes functions
for chronological modeling and dating of archaeological assemblages from
count data. It provides methods for matrix seriation. It also allows to
compute time point estimates and density estimates of the occupation and
duration of an archaeological site. **kairos** provides methods for:

- Matrix seriation:
`seriate_rank()`

and`seriate_average()`

- Mean ceramic date estimation (South 1977):
`mcd()`

- Event and accumulation date estimation (Bellanger and Husi 2012):
`event()`

- Aoristic analysis (Ratcliffe 2000):
`aoristic()`

- Chronological apportioning (Roberts et al. 2012):
`apportion()`

**tabula** is a companion
package to **kairos** that provides functions for visualization and
analysis of archaeological count data.

You can install the released version of **kairos** from
CRAN with:

```
install.packages("kairos")
```

And the development version from GitHub with:

```
# install.packages("remotes")
remotes::install_github("tesselle/kairos")
```

```
## Load packages
library(khroma) # Colour schemes
library(tabula) # Plot methods
library(kairos)
```

**kairos** only supports dates expressed in CE years (BCE years must be
given as negative numbers). **All results are rounded to zero decimal
places** (sub-annual precision does not make sense in most situations).
You can change this behavior with `options(kairos.precision = x)`

(for
`x`

decimal places).

*It assumes that you keep your data tidy*: each variable (type/taxa)
must be saved in its own column and each observation (sample/case) must
be saved in its own row.

```
## Build an incidence matrix with random data
set.seed(12345)
incidence1 <- matrix(sample(0:1, 400, TRUE, c(0.6, 0.4)), nrow = 20)
incidence1 <- incidence1 > 0 # logical
## Get seriation order on rows and columns
(indices <- seriate_rank(incidence1, margin = c(1, 2), stop = 100))
#> <RankPermutationOrder>
#> Permutation order for matrix seriation:
#> - Row order: 1 4 20 3 9 16 19 10 13 2 11 7 17 5 6 18 14 15 8 12...
#> - Column order: 1 16 9 4 8 14 3 20 13 2 6 18 7 17 5 11 19 12 15 10...
## Permute rows and columns
incidence2 <- permute(incidence1, indices)
## Plot matrix
tabula::plot_heatmap(incidence1) +
khroma::scale_fill_logical()
tabula::plot_heatmap(incidence2) +
khroma::scale_fill_logical()
```

```
## Aoristic Analysis
data("loire", package = "folio")
loire <- subset(loire, area %in% c("Anjou", "Blésois", "Orléanais", "Haut-Poitou", "Touraine"))
## Get time range
loire_range <- loire[, c("lower", "upper")]
## Calculate aoristic sum (weights) by group
aorist_groups <- aoristic(loire_range, step = 50, weight = TRUE,
groups = loire$area)
plot(aorist_groups)
```

```
## Rate of change by group
roc_groups <- roc(aorist_groups, n = 30)
plot(roc_groups)
```

Please note that the **kairos** project is released with a Contributor
Code of Conduct. By contributing
to this project, you agree to abide by its terms.

Bellanger, Lise, and Philippe Husi. 2012. “Statistical Tool for Dating
and Interpreting Archaeological Contexts Using Pottery.” *Journal of
Archaeological Science* 39 (4): 777–90.
.

Ratcliffe, Jerry H. 2000. “Aoristic Analysis: The Spatial Interpretation
of Unspecific Temporal Events.” *International Journal of Geographical
Information Science* 14 (7): 669–79.
.

Roberts, John M., Barbara J. Mills, Jeffery J. Clark, W. Randall Haas,
Deborah L. Huntley, and Meaghan A. Trowbridge. 2012. “A Method for
Chronological Apportioning of Ceramic Assemblages.” *Journal of
Archaeological Science* 39 (5): 1513–20.
.

South, S. A. 1977. *Method and Theory in Historical Archaeology*.
Studies in Archeology. New York: Academic Press.

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