quant: Quantification of binary capture histories

In BBRecapture: Bayesian Behavioural Capture-Recapture Models

Description

The quant.binary family of functions allow to quantify binary capture histories (partial or complete) in terms of a meaningful quantity which can be interpreted as a possibly meaningful behavioral covariate (like memory persistence of previous capture history)

Usage

quant.binary.integer(x)

quant.binary(x)

quant.binary.markov(x, markov.ord)

quant.binary.counts(x)

quant.binary.counts.integer(x)

Arguments

x	either a character string or a numeric vector exclusively made by binary entries 0 or 1.
markov.ord	a positive integer representing the order of the Markovian structure which one is willing to reproduce with suitable partition of the unit interval and the quantification of capture history standardized in the unit interval

Details

For a more detailed description of instances of meaningful behavioral covariates see Alunni Fegatelli and Tardella (2012) and Alunni Fegatelli (2013)[PhD Thesis]

Value

For quant.binary it returns a numeric value within the unit interval [0,1] and
quant.binary.markov. For quant.binary.integer it returns an integer value.

Examples

## Example of quantification with character input

capt.hist="0110"

quant.binary(capt.hist)
quant.binary.markov(capt.hist,markov.ord=2)
quant.binary.integer(capt.hist)
quant.binary.counts(capt.hist)
quant.binary.counts.integer(capt.hist)

## Example of quantification with numeric input

ch=c(0,1,1,0)
quant.binary(ch)
quant.binary.markov(ch,markov.ord=2)
quant.binary.integer(ch)
quant.binary.counts(ch)
quant.binary.counts.integer(ch)

BBRecapture documentation built on March 26, 2020, 7:31 p.m.