Produces an abundance vs time diagram.
# S4 method for IncrementTest,missing plot( x, calendar = getOption("kairos.calendar"), col.neutral = "#004488", col.selection = "#BB5566", col.roll = "grey", flip = FALSE, ncol = NULL, xlab = NULL, ylab = NULL, main = NULL, sub = NULL, ann = graphics::par("ann"), axes = TRUE, frame.plot = axes, ... )
IncrementTestobject to be plotted.
TimeScaleobject specifying the target calendar (see
- col.neutral, col.selection, col.roll
A vector of colors.
logicalscalar: should the y-axis (ticks and numbering) be flipped from side 2 (left) to 4 (right) from series to series when
integerspecifying the number of columns to use when
multiple". Defaults to 1 for up to 4 series, otherwise to 2.
- xlab, ylab
charactervector giving the x and y axis labels.
characterstring giving a main title for the plot.
characterstring giving a subtitle for the plot.
logicalscalar: should the default annotation (title and x and y axis labels) appear on the plot?
logicalscalar: should axes be drawn on the plot?
logicalscalar: should a box be drawn around the plot?
Further parameters to be passed to
panel(e.g. graphical parameters).
plot() is called it for its side-effects: it results in a graphic being
displayed (invisibly returns
Results of the frequency increment test can be displayed on an abundance
vs time diagram aid in the detection and quantification of selective
processes in the archaeological record. If
TRUE, each time
series is subsetted according to
window to see if episodes of selection
can be identified among decoration types that might not show overall
selection. If so, shading highlights the data points where
fit() identifies selection.
Displaying FIT results on an abundance vs time diagram is adapted from Ben Marwick's original idea.
## Data from Crema et al. 2016 data("merzbach", package = "folio") ## Keep only decoration types that have a maximum frequency of at least 50 keep <- apply(X = merzbach, MARGIN = 2, FUN = function(x) max(x) >= 50) counts <- merzbach[, keep] ## Group by phase ## We use the row names as time coordinates (roman numerals) dates <- as.numeric(utils::as.roman(rownames(counts))) ## Frequency Increment Test freq <- fit(counts, dates, calendar = NULL) ## Plot time vs abundance plot(freq, calendar = NULL, ncol = 3, xlab = "Phases") ## Plot time vs abundance and highlight selection freq <- fit(counts, dates, calendar = NULL, roll = TRUE, window = 5) plot(freq, calendar = NULL, ncol = 3, xlab = "Phases")