jackknife.MeanDate {kairos} | R Documentation |
Jackknife Mean Ceramic Dates
Description
Generate jackknife estimations of an MCD.
Usage
## S4 method for signature 'MeanDate'
jackknife(object, f = NULL, calendar = get_calendar())
Arguments
object |
|
f |
A |
calendar |
An |
Value
If f
is NULL
, jackknife()
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 jackknife estimate of mean.
bias
The jackknife estimate of bias.
error
The jackknife estimate of standard erro.
Author(s)
N. Frerebeau
See Also
Other resampling methods:
bootstrap.EventDate
,
bootstrap.MeanDate
,
jackknife.EventDate
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))
## Get MCD in years CE
time(mc_dates, calendar = CE())
## Bootstrap resampling
boot <- bootstrap(mc_dates, n = 30)
head(boot)
## Jackknife resampling
jack <- jackknife(mc_dates)
head(jack)
## 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)))
[Package kairos version 2.3.0 Index]