An S4 class to store the event and accumulation times of archaeological assemblages as well as the results of resampling methods for date model checking.
# S4 method for DateModel
[[(x, i)# S4 method for DateModel
[(x, i, j, drop = TRUE)
A DateModel object from which to extract element(s).
Indices specifying elements to extract.
i is a character string matching to the name of a slot.
j can be missing or NULL,
a numeric or character vector.
Numeric values are coerced to integer as by
as.integer (and hence truncated towards zero).
Character vectors will be matched to the names of the object.
A logical scalar: should the result be coerced to
the lowest possible dimension?
[[: Extracts informations from a slot selected by subscript
i.
[: Allows to select a slot thru j.
countsA numeric matrix of count data.
datesA two columns data.frame giving the known dates
used for model fitting and an identifier to link each row to an assemblage.
levelA length-one numeric vector giving the
confidence level.
modelA multiple linear model: the Gaussian
multiple linear regression model fitted for event date estimation and
prediction.
residualA length-one numeric vector giving the residual
standard deviation.
rowsA five columns data.frame giving the predicted event
dates for each archaeological assemblage, with the following columns:
An identifier to link each row to an assemblage.
The event date estimation.
The lower boundary of the confidence interval.
The upper boundary of the confidence interval.
The standard error of predicted dates.
columnsA five columns data.frame giving the predicted
event dates for each archaeological type or fabric, with the following
columns:
An identifier to link each row to an assemblage.
The event date estimation.
The lower boundary of the confidence interval.
The upper boundary of the confidence interval.
The standard error of predicted dates.
accumulationA two columns data.frame giving the point
estimate of accumulation dates of archaeological assemblages and an
identifier to link each row to an assemblage.
jackknifeA six columns data.frame giving the results of
the resamping procedure (jackknifing fabrics) for each assemblage (in rows)
with the following columns:
An identifier to link each row to an assemblage.
The jackknife event date estimate.
The lower boundary of the associated prediction interval.
The upper boundary of the associated prediction interval.
The standard error of predicted means.
The jackknife estimate of bias.
bootstrapA six columns data.frame giving the boostrap
distribution statistics for each replicated assemblage (in rows)
with the following columns:
An identifier to link each row to an assemblage.
Minimum value.
Sample quantile to 0.05 probability.
Mean value (event date).
Sample quantile to 0.95 probability.
Maximum value.