simulate: Measure Diversity by Comparing to Simulated Assemblages

In tabula: Analysis and Visualization of Archaeological Count Data

Measure Diversity by Comparing to Simulated Assemblages

Description

Measure Diversity by Comparing to Simulated Assemblages

Usage

## S4 method for signature 'DiversityIndex'
simulate(
  object,
  n = 1000,
  step = 1,
  interval = c("percentiles", "student", "normal"),
  level = 0.8,
  progress = getOption("tabula.progress")
)

Arguments

object	A DiversityIndex object.
n	A non-negative integer giving the number of bootstrap replications.
step	An integer giving the increment of the sample size.
interval	A character string giving the type of confidence interval to be returned. It must be one "percentiles" (sample quantiles, as described in Kintigh 1984; the default), "student" or "normal". Any unambiguous substring can be given.
level	A length-one numeric vector giving the confidence level.
progress	A logical scalar: should a progress bar be displayed?

Value

Returns a DiversityIndex object.

Author(s)

N. Frerebeau

References

Baxter, M. J. (2001). Methodological Issues in the Study of Assemblage Diversity. American Antiquity, 66(4), 715-725. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/2694184")}.

Kintigh, K. W. (1984). Measuring Archaeological Diversity by Comparison with Simulated Assemblages. American Antiquity, 49(1), 44-54. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/280511")}.

See Also

plot(), resample()

Other diversity measures: heterogeneity(), occurrence(), rarefaction(), richness(), similarity(), turnover()

Examples

## Data from Conkey 1980, Kintigh 1989
data("cantabria")

## Assemblage diversity size comparison
## Warning: this may take a few seconds!
h <- heterogeneity(cantabria, method = "shannon")
h_sim <- simulate(h)
plot(h_sim)

r <- richness(cantabria, method = "count")
r_sim <- simulate(r)
plot(r_sim)

tabula documentation built on Aug. 22, 2023, 5:11 p.m.