stats_bootstrap

A <code><a rd-options="" href="/link/function?package=tabula&version=1.6.1" data-mini-rdoc="tabula::function">function</a></code> that takes <code>x</code> as an argument
and returns a single numeric value.

A <code><a rd-options="" href="/link/numeric?package=tabula&version=1.6.1" data-mini-rdoc="tabula::numeric">numeric</a></code> vector of probabilities with values in
\([0,1]\) (see <code><a rd-options="stats:quantile" href="/link/stats%3A%3Aquantile()?package=tabula&version=1.6.1&to=stats%3Aquantile" data-mini-rdoc="stats:quantile::stats::quantile()">stats::quantile()</a></code>).

probs

A non-negative <code><a rd-options="" href="/link/integer?package=tabula&version=1.6.1" data-mini-rdoc="tabula::integer">integer</a></code> giving the number of bootstrap
replications.

A <code><a rd-options="" href="/link/logical?package=tabula&version=1.6.1" data-mini-rdoc="tabula::logical">logical</a></code> scalar: should missing values be removed
from <code>x</code> before the quantiles are computed?

na.rm

Extra arguments passed to <code>do</code>.

internal

An easy way to examine archaeological count data. This
package provides a convenient and reproducible toolkit for relative
dating by matrix seriation (reciprocal ranking, CA-based seriation).
It also provides several tests and measures of diversity:
heterogeneity and evenness (Brillouin, Shannon, Simpson, etc.),
richness and rarefaction (Chao1, Chao2, ACE, ICE, etc.), turnover and
similarity (Brainerd-Robinson, etc.). The package make it easy to
visualize count data and statistical thresholds: rank vs abundance
plots, heatmaps, Ford (1962) and Bertin (1977) diagrams.

Nicolas Frerebeau

tabula

Analysis, Seriation and Visualization of Archaeological Count
Data

Brice Lebrun

Matthew Peeples

Ben Marwick

Anne Philippe

Jean-Baptiste Fourvel

stats_bootstrap function

A <code><a rd-options='' href='function'>function</a></code> that takes <code>x</code> as an argument
and returns a single numeric value.

A <code><a rd-options='' href='numeric'>numeric</a></code> vector of probabilities with values in
\([0,1]\) (see <code><a rd-options='stats:quantile' href='stats::quantile()'>stats::quantile()</a></code>).

A non-negative <code><a rd-options='' href='integer'>integer</a></code> giving the number of bootstrap
replications.

A <code><a rd-options='' href='logical'>logical</a></code> scalar: should missing values be removed
from <code>x</code> before the quantiles are computed?

stats_bootstrap: Bootstrap Estimation

Description

Usage

Arguments

Value