distanceSampling: Fit data of distance sampling using the best combination of...

In Xinhai-Li/abundanceR: Estimate wildlife abundance based on distance sampling and species distribution models

Fit data of distance sampling using the best combination of Key and Adjustment

Description

This function ranks the 9 combinations of Key and Adjustment in distance sampling

Usage

distanceSampling(survey)

Arguments

survey

A data.frame with columns 'species', 'size', 'distance', 'Region.Label', 'Effort'

Author(s)

Xinhai Li ([e-mail])

Examples

 attach(distancesampling)
 AICs = distanceSampling(distancesampling)
 AICs
 ds.kiang <- ds(kiang, key = AICs$Key[2], adjustment = AICs$Adjustment[2], convert.units = 0.001) # truncation=1000
 summary(ds.kiang)
 SM = summary(ds.kiang)
 Average.p = SM[[3]][[14]][1]
 plot(ds.kiang, main="Detection rate\n Tibetan wild ass, half-normal detection function")

Xinhai-Li/abundanceR documentation built on Feb. 1, 2024, 4:47 a.m.