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Rdistance (version 4.3.0)

Density and Abundance from Distance-Sampling Surveys

Description

Distance-sampling () is a field survey and analytical method that estimates density and abundance of survey targets (e.g., animals) when detection probability declines with observation distance. Distance-sampling is popular in ecology, especially when survey targets are observed from aerial platforms (e.g., airplane or drone), surface vessels (e.g., boat or truck), or along walking transects. Analysis involves fitting smooth (parametric) curves to histograms of observation distances and using those functions to adjust density estimates for missed targets. Routines included here fit curves to observation distance histograms, estimate effective sampling area, density of targets in surveyed areas, and the abundance of targets in a surrounding study area. Confidence interval estimation uses built-in bootstrap resampling. Help files are extensive and have been vetted by multiple authors. Many tutorials are available on the package's website (URL below).

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Version

Install

install.packages('Rdistance')

Monthly Downloads

520

Version

4.3.0

License

GNU General Public License

Maintainer

Trent McDonald

Last Published

January 10th, 2026

Functions in Rdistance (4.3.0)

Observation distances

dfuncEstimErrMessage

dfuncEstim error messages

effectiveDistance

Effective sampling distances

Coefficients of an estimated detection function

differentiableLikelihoods

Differentiable likelihoods in Rdistance

cosine.expansion

Cosine expansion terms

Add color to result if terminal accepts it

Estimate a distance-based detection function

Estimate single-observer line-transect distance function

Estimate multiple-observer line-transect distance functions

Unknown error message

Effort information

Half-normal distance function

Estimate g(0) or g(x)

Distance function expansion terms

Abundance point estimates

Set number of cores

Hazard rate likelihood

halfnorm.start.limits

Start and limit values for halfnorm distance function

insertOneStepBreaks

Insert oneStep Likelihood breaks

hermite.expansion

Hermite expansion factors

Compute and print distance function integration

integrateHazrateLines

Integrate Hazard-rate line survey distance functions

integrateDfuncs

Integration of distance functions

integrateHalfnormPoints

Integrate Half-normal Point transects

hazrate.start.limits

Start and limit values for hazrate distance function

integrateHalfnormLines

Integrate Half-normal line surveys

integrateNegexpLines

Integrate Negative exponential

integrateOneStepPoints

Integrate Point-survey One-step function

integrateOneStepNumeric

Numeric Integration of One-step Function

integrateNegexpPoints

Integrate Negative exponential point surveys

integrateOneStepLines

Integrate Line-transect One-step function

integrateGammaLines

Integrate Gamma line surveys

integrateNumeric

Numeric Integration

Check RdistDf data frames

Tests for smoothed distance functions

Detect intercept-only distance function

Tests for point surveys

Test whether object is unitless

Likelihood parameter names

model.matrix.dfunc

Rdistance model matrix

negexp.start.limits

Start and limit values for negexp distance function

Find coordinate of function maximum

Negative exponential likelihood

Negative log likelihood of distances

Number of covariates

observationType

Type of observations

lines.dfunc - Line plotting method for distance functions

Predict distance functions

Calculations for one bootstrap iteration

Compute off-transect distances from sighting distances and angles

Density on transects

Distance function maximum likelihood estimates

Distance function values at observations

plot.dfunc.para

Plot parametric distance functions

Plot method for distance (detection) functions

Parse Rdistance model

oneStep.start.limits

oneStep likelihood start and limit values

sparrowDfuncObserver

Brewer's Sparrow detection function

Brewer's Sparrow detection data frame in Rdistance >4.0.0 format.

Predict distance functions

Mixture of two uniforms likelihood

Print abundance estimates

simple.expansion

Simple polynomial expansion factors

Simpson numerical integration coefficients

Sage Thrasher detection data frame in Rdistance >4.0.0 format

Summarize a distance function object

thrasherSiteData

Sage Thrasher site data.

Sine expansion terms

sparrowDetectionData

Brewer's Sparrow detection data

Summarize abundance estimates

Numeric second derivatives

Type of transects

summary.rowwise_df

Summary method for Rdistance data frames

Print method for distance function object

Unit assignment helpers

sparrowSiteData

Brewer's Sparrow site data

thrasherDetectionData

Sage Thrasher detection data

Unnest an RdistDf data frame

Estimate variance-covariance

Distance function starting values and limits

Modes of the Gamma distribution

Reparameterise Gamma parameters for use in dgamma

'nlminb' optimizer

Gamma distance function

'nlminb' optimizer

AIC-related fit statistics for detection functions

'optim' optimizer

Gamma.start.limits

Gamma.start.limits - Start and limit values for Gamma distance function

Effective Detection Radius (EDR) for point transects

Effective Strip Width (ESW) for line transects

Automated classical distance analysis

Perform bootstrap iterations

Rdistance-package

Rdistance - Distance Sampling Analyses for Abundance Estimation

RdistanceControls

Rdistance optimization control parameters.

Bias corrected bootstraps

bspline.expansion

B-spline expansion terms

Check for the presence of units

Distance Sampling Abundance Estimates

Check number of numeric integration intervals

Construct Rdistance nested data frames