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Kernel density estimation of calendar probability distributions

Source: R/cal_aggregate.R
cal_density.Rd

Aggregates calibrated radiocarbon dates and other calendar probability distributions using the composite kernel density estimate (cKDE) method method Brown2017c14. This involves estimating the density of a set of dates by repeatedly computing the kernel density estimate of a random sample of ages drawn from their probability distributions.

Usage

cal_density(x, bw = 30, ..., times = 25, bootstrap = TRUE, strata = NULL)

# S3 method for class 'c14_cal'
density(x, ...)

Arguments

x

A cal vector of calendar probability distributions

bw

Kernel bandwidth size passed to stats::density(). Can be either an integer value or a character selection rule, but the latter will likely result in a different bandwidth being applied to each bootstrapped sample and therefore should be avoided. Default: 30 (years).

...

Further arguments passed to stats::density()

times

Number of bootstrap samples to generate. The default of 25 is suitable for testing but should be set much higher in practice.

bootstrap

If TRUE (the default), randomly resamples with replacement from x before each KDE calculation.

strata

If not NULL, KDEs will be weighted to ensure equal representation of classes specified by a factor or character vector. If bootstrap = TRUE, bootstrap samples are generated using stratified resampling of the same classes.

Value

The result as a data frame or tibble::tibble with three columns: age (interpolated to common range of x), .estimate (mean of the bootstrapped KDEs), and .error (standard error of the bootstrapped KDEs).

Details

cal_density(..., bootstrap = TRUE) performs composite kernel density estimation with bootstrapping McLaughlin2019c14, where sampling error. x is estimated by randomly resampling x before each KDE calculation.

See McLaughlin2019;textualc14 and Crema2022;textualc14 for discussions of bandwith selection.

References

See also

Other functions for aggregating calendar probability distributions: cal_sum()

Examples

data(shub1_c14)
shub1_cal <- c14_calibrate(shub1_c14$c14_age, shub1_c14$c14_error)
cal_density(shub1_cal)
#> # A tibble: 14,331 × 3
#>           age  .estimate    .error
#>          <yr>      <dbl>     <dbl>
#>  1 930 cal BP 0.00000583 0.0000291
#>  2 931 cal BP 0.00000613 0.0000306
#>  3 932 cal BP 0.00000644 0.0000321
#>  4 933 cal BP 0.00000674 0.0000336
#>  5 934 cal BP 0.00000705 0.0000351
#>  6 935 cal BP 0.00000735 0.0000366
#>  7 936 cal BP 0.00000766 0.0000381
#>  8 937 cal BP 0.00000796 0.0000396
#>  9 938 cal BP 0.00000827 0.0000411
#> 10 939 cal BP 0.00000857 0.0000426
#> # ℹ 14,321 more rows

# Stratify and weight bootstrap estimation by phase
cal_density(shub1_cal, strata = shub1_c14$phase)
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> Warning: sum(weights) != 1  -- will not get true density
#> # A tibble: 14,331 × 3
#>           age .estimate    .error
#>          <yr>     <dbl>     <dbl>
#>  1 930 cal BP 0.0000184 0.0000727
#>  2 931 cal BP 0.0000202 0.0000790
#>  3 932 cal BP 0.0000220 0.0000852
#>  4 933 cal BP 0.0000238 0.0000914
#>  5 934 cal BP 0.0000256 0.0000977
#>  6 935 cal BP 0.0000274 0.000104 
#>  7 936 cal BP 0.0000292 0.000110 
#>  8 937 cal BP 0.0000310 0.000116 
#>  9 938 cal BP 0.0000328 0.000123 
#> 10 939 cal BP 0.0000346 0.000129 
#> # ℹ 14,321 more rows