effectiveDistance: Effective sampling distances

In Rdistance: Density and Abundance from Distance-Sampling Surveys

Effective sampling distances

Description

Computes Effective Strip Width (ESW) for line-transect detection functions, or the analogous Effective Detection Radius (EDR) for point-transect detection functions.

Usage

effectiveDistance(object, newdata = NULL)

Arguments

object	An Rdistance model frame or fitted distance function, normally produced by a call to dfuncEstim.
newdata	A data frame containing new values for covariates at which either ESW's or EDR's will be computed. If NULL and object contains covariates, the covariates stored in object are used (like predict.lm). If not NULL, covariate values in newdata are used. See Value section for more information.

Details

Serves as a wrapper for ESW and EDR.

Effective distances are areas under scaled distance functions (i.e., area under g(x)). Areas are exact for functions whose integral is known (e.g., negexp). Numeric integration is used for all others.

Value

If newdata is present, the returned value is a vector of effective sampling distances associated with covariate values in newdata. Length of return in this case is the number of rows in newdata. If newdata is NULL, the returned value is a vector of effective sampling distances associated with covariate values in object. Length of return in this case is the number of detected groups. The returned vector has measurement units, i.e., object$outputUnits.

See Also

dfuncEstim, ESW, EDR, integrateNumeric, integrateNegexpLines

Rdistance documentation built on Jan. 10, 2026, 1:07 a.m.