optima: Weighted averaging optima and tolerance ranges

In analogue: Analogue and Weighted Averaging Methods for Palaeoecology

Weighted averaging optima and tolerance ranges

Description

Computes weighted average optima and tolerance ranges from species abundances and values of the environment.

Usage

optima(x, ...)

## Default S3 method:
optima(x, env, boot = FALSE, nboot = 1000,
       alpha = 0.05, ...)

## Default S3 method:
tolerance(x, env, useN2 = TRUE, ...)

Arguments

x	Species data matrix or data frame.
env	Numeric; variable for which optima or tolerances are required.
boot, nboot	logical (boot), numeric (nboot); should bootstrap resampling be employed to estimate the optima, and if so how many bootstrap samples to draw?
alpha	numeric; 1 - alpha gives the coverage for the percentile bootstrap confidence interval.
useN2	logical; should Hill's N2 values be used to produce un-biased tolerances?
...	Arguments passed to other methods.

Value

Both functions return a named vector containing the WA optima or tolerances for the environmental gradient specified by env.

Note

Objects of class "optima" or "tolerance" can be coerced to data frames using methods for as.data.frame.

Author(s)

Gavin L. Simpson

See Also

wa

Examples

## Load the Imbrie & Kipp data and
## summer sea-surface temperatures
data(ImbrieKipp)
data(SumSST)

## WA optima
(opt <- optima(ImbrieKipp, SumSST))

## WA tolerances
(tol <- tolerance(ImbrieKipp, SumSST, useN2 = TRUE))

## caterpillar plot
caterpillarPlot(opt, tol)

## convert to data frame
as.data.frame(opt)
as.data.frame(tol)

## bootstrap WA optima - 100 resamples too low for SD & pCI
bopt <- optima(ImbrieKipp, SumSST, boot = TRUE, nboot = 100)
head(bopt)

analogue documentation built on June 25, 2025, 5:09 p.m.