Bootstrap Mean Ceramic Dates

Generates bootstrap estimations of an MCD.

Usage

# S4 method for class 'MeanDate'
bootstrap(
  object,
  n = 1000,
  f = NULL,
  level = 0.95,
  interval = c("basic", "normal", "percentiles"),
  seed = NULL,
  calendar = get_calendar()
)

Arguments

object: A MeanDate object (typically returned by mcd()).
n: A non-negative integer specifying the number of bootstrap replications.
f: A function that takes a single numeric vector (the result of the resampling procedure) as argument.
level: A length-one numeric vector giving the confidence level. Must be a single number between \(0\) and \(1\). Only used if f is NULL.
interval: A character string giving the type of confidence interval to be returned. It must be one "basic" (the default), "normal" or "percentiles" (see arkhe::confidence_bootstrap()). Any unambiguous substring can be given. Only used if f is NULL.
seed: An object specifying if and how the random number generator should be initialized (see stats::simulate()).
calendar: An aion::TimeScale object specifying the target calendar (see aion::calendar()).

Value

If f is NULL, bootstrap() returns a data.frame with the following elements (else, returns the result of f applied to the n resampled values) :

original: The observed value.
mean: The bootstrap estimate of mean.
bias: The bootstrap estimate of bias.
error: The boostrap estimate of standard error.
lower: The lower limit of the bootstrap confidence interval at level.
upper: The upper limit of the bootstrap confidence interval at level.

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 757.291 CE and 1259.38 CE

## 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

## Bootstrap resampling
boot <- bootstrap(mc_dates, n = 30)
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
#> Warning: Extreme order statistics used as endpoints.
head(boot)
#>         original      mean       bias    error    lower     upper
#> LZ0789  757.2917  757.6215  0.3298611 13.62395 717.7083  777.0833
#> LZ0783  796.6667  795.9444 -0.7222222 33.45576 748.3333  855.8333
#> LZ0782  797.5000  794.4706 -3.0294118 11.30521 775.0000  820.8824
#> LZ0778  952.5862  965.6322 13.0459770 32.62280 850.4310 1006.0345
#> LZ0777  996.2963  998.2253  1.9290123 20.59349 962.0370 1035.8796
#> LZ0776 1016.0714 1016.2202  0.1488095 42.04516 923.2143 1122.3214

## 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

## Plot
plot(mc_dates, decreasing = FALSE)
## Add bootstrap confidence intervals
segments(x0 = boot$lower, y0 = seq_len(nrow(boot)),
         x1 = boot$upper, y1 = seq_len(nrow(boot)))

Usage

Arguments

Value

See also

Author

Examples