transect.intensity: Compute expected and observed counts by distance within...
In DSpat: Spatial Modelling for Distance Sampling Data

Description Usage Arguments Details Value Author(s)

Computes the expected and observed counts for equally-spaced bins of perpendincular distance within each transect. Expected and observed counts are each a matrix with a row for each transect and a column for each distance bin.

1	transect.intensity(x, epsvu=NULL, obs.ppp, covariates, nclass=NULL, width)

`x`	dspat object
`epsvu`	epsvu setting for fitted model; only uses epsvu[2] value for u
`obs.ppp`	observation point process
`covariates`	dataframe of covariates at quadrature points
`nclass`	number of equally-spaced distance intervals within 0-width/2
`width`	maximum full transect width over all transects

The actual number of distance bins will only match nclass if it is selected such that nclass*epsvu[2] is an even multiple of width/2. The function dspat adjusts epsvu[2] such that it is an even multiple of width/2 and this function assumes that condition holds. Sometimes your choice of epsvu[2] will provide less than optimal choices for nclass and in some cases it can only choose a single bin. In these cases, select another value of epsvu[2] which is a multiple for width/2.

If nclass is not specified then it uses the default of ceiling(sqrt(n)) intervals.

`exp.counts`	matrix of expected counts in each distance bin (columns) for each transect (row)
`obs.counts`	matrix of observed counts in each distance bin (columns) for each transect (row)

Jeff Laake

DSpat documentation built on May 2, 2019, 11:10 a.m.