MCD Plot

MCD Plot

Usage

# S4 method for MeanDate,missing
plot(
  x,
  calendar = getOption("kairos.calendar"),
  decreasing = TRUE,
  main = NULL,
  sub = NULL,
  ann = graphics::par("ann"),
  axes = TRUE,
  frame.plot = axes,
  panel.first = NULL,
  panel.last = NULL,
  ...
)

# S4 method for SimulationMeanDate,missing
plot(
  x,
  calendar = getOption("kairos.calendar"),
  interval = "student",
  level = 0.8,
  decreasing = TRUE,
  main = NULL,
  sub = NULL,
  ann = graphics::par("ann"),
  axes = TRUE,
  frame.plot = axes,
  panel.first = NULL,
  panel.last = NULL,
  ...
)

Arguments

x

A MeanDate object.

calendar

A TimeScale object specifying the target calendar (see calendar()).

decreasing

A logical scalar: should the sort be increasing or decreasing?

main

A character string giving a main title for the plot.

sub

A character string giving a subtitle for the plot.

ann

A logical scalar: should the default annotation (title and x, y and z axis labels) appear on the plot?

axes

A logical scalar: should axes be drawn on the plot?

frame.plot

A logical scalar: should a box be drawn around the plot?

panel.first

An an expression to be evaluated after the plot axes are set up but before any plotting takes place. This can be useful for drawing background grids.

panel.last

An expression to be evaluated after plotting has taken place but before the axes, title and box are added.

...

Further graphical parameters.

interval

A character string giving the type of confidence interval to be returned. It must be one "student" (the default), "normal", "percentiles" or "range" (min-max). Any unambiguous substring can be given.

level

A length-one numeric vector giving the confidence level. Only used if interval is not "range".

Value

plot() is called it for its side-effects: it results in a graphic being displayed (invisibly returns x).

See also

mcd()

Other plotting methods: plot_aoristic, plot_event, plot_fit, plot_time()

Author

N. Frerebeau

Examples

## Data from Peeples and Schachner 2012
data("zuni", package = "folio")

## Set the start and end dates for each ceramic type
dates <- list(
  LINO = c(600, 875), KIAT = c(850, 950), RED = c(900, 1050),
  GALL = c(1025, 1125), ESC = c(1050, 1150), PUBW = c(1050, 1150),
  RES = c(1000, 1200), TULA = c(1175, 1300), PINE = c(1275, 1350),
  PUBR = c(1000, 1200), WING = c(1100, 1200), WIPO = c(1125, 1225),
  SJ = c(1200, 1300), LSJ = c(1250, 1300), SPR = c(1250, 1300),
  PINER = c(1275, 1325), HESH = c(1275, 1450), KWAK = c(1275, 1450)
)

## Calculate date midpoints
mid <- vapply(X = dates, FUN = mean, FUN.VALUE = numeric(1))

## Calculate MCD
(mc_dates <- mcd(zuni[100:125, ], dates = mid))
#> 26 x 18 x 1 time series observed between 276230.3 and 459613.1 r.d.

## Get MCD in years CE
time(mc_dates, calendar = CE())
#>  [1]  757.2912  796.6659  797.4991  952.5855  996.2952 1016.0738 1027.5011
#>  [8] 1059.5249 1073.6597 1075.5213 1089.5820 1092.8564 1100.0000 1127.7799
#> [15] 1137.1101 1200.0017 1204.3868 1207.1436 1219.4454 1227.3745 1235.4176
#> [22] 1237.5000 1238.8896 1253.1241 1256.2502 1259.3757

## Plot
plot(mc_dates)


## Bootstrap resampling
boot <- bootstrap(mc_dates, n = 30)
head(boot)
#>         original      mean       bias     error
#> LZ0789  757.2917       NaN        NaN        NA
#> LZ0783  796.6667  858.4295 61.7628395 121.16457
#> LZ0782  797.5000  871.5139 74.0139084  98.12367
#> LZ0778  952.5862  952.3055 -0.2807372 109.08688
#> LZ0777  996.2963 1011.9250 15.6286638  87.38330
#> LZ0776 1016.0714 1012.1865 -3.8849198  75.93731

## Jackknife resampling
jack <- jackknife(mc_dates)
head(jack)
#>         original      mean       bias    error
#> LZ0789  757.2917  768.2870 186.921296 207.5535
#> LZ0783  796.6667  806.9974 175.621693 228.0861
#> LZ0782  797.5000  804.1715 113.415558 169.0563
#> LZ0778  952.5862  954.5205  32.882529 138.6064
#> LZ0777  996.2963  996.6640   6.251785 111.0144
#> LZ0776 1016.0714 1017.1652  18.594831  72.6602

## Simulation
sim <- simulate(mc_dates, nsim = 30)
plot(sim, interval = "range", pch = 16)