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Rdistance (version 4.3.1)

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

434

Version

4.3.1

License

GNU General Public License

Maintainer

Trent McDonald

Last Published

February 11th, 2026

Functions in Rdistance (4.3.1)

Bias corrected bootstraps

bspline.expansion

B-spline expansion terms

Construct Rdistance nested data frames

Check number of numeric integration intervals

Automated classical distance analysis

Perform bootstrap iterations

Rdistance-package

Rdistance - Distance Sampling Analyses for Abundance Estimation

Check for the presence of units

RdistanceControls

Rdistance optimization control parameters.

Distance Sampling Abundance Estimates

Observation distances

Coefficients of an estimated detection function

Estimate single-observer line-transect distance function

Estimate multiple-observer line-transect distance functions

cosine.expansion

Cosine expansion terms

effectiveDistance

Effective sampling distances

differentiableLikelihoods

Differentiable likelihoods in Rdistance

Add color to result if terminal accepts it

dfuncEstimErrMessage

dfuncEstim error messages

Estimate a distance-based detection function

Half-normal distance function

Unknown error message

Effort information

Distance function expansion terms

halfnorm.start.limits

Start and limit values for halfnorm distance function

Hazard rate likelihood

Estimate g(0) or g(x)

Abundance point estimates

Set number of cores

insertOneStepBreaks

Insert oneStep Likelihood breaks

integrateGammaLines

Integrate Gamma line surveys

integrateHalfnormLines

Integrate Half-normal line surveys

integrateHalfnormPoints

Integrate Half-normal Point transects

integrateHazrateLines

Integrate Hazard-rate line survey distance functions

Compute and print distance function integration

integrateDfuncs

Integration of distance functions

hermite.expansion

Hermite expansion factors

hazrate.start.limits

Start and limit values for hazrate distance function

integrateNegexpLines

Integrate Negative exponential

Tests for smoothed distance functions

integrateNegexpPoints

Integrate Negative exponential point surveys

Tests for point surveys

integrateNumeric

Numeric Integration

integrateOneStepLines

Integrate Line-transect One-step function

Check RdistDf data frames

Test whether object is unitless

Detect intercept-only distance function

integrateOneStepPoints

Integrate Point-survey One-step function

integrateOneStepNumeric

Numeric Integration of One-step Function

Number of covariates

Negative exponential likelihood

observationType

Type of observations

Find coordinate of function maximum

model.matrix.dfunc

Rdistance model matrix

Distance function maximum likelihood estimates

negexp.start.limits

Start and limit values for negexp distance function

Likelihood parameter names

lines.dfunc - Line plotting method for distance functions

Negative log likelihood of distances

Density on transects

oneStep.start.limits

oneStep likelihood start and limit values

Predict distance functions

plot.dfunc.para

Plot parametric distance functions

Distance function values at observations

Calculations for one bootstrap iteration

Compute off-transect distances from sighting distances and angles

Mixture of two uniforms likelihood

Parse Rdistance model

Plot method for distance (detection) functions

Print abundance estimates

sparrowDetectionData

Brewer's Sparrow detection data

Numeric second derivatives

Simpson numerical integration coefficients

Sine expansion terms

sparrowDfuncObserver

Brewer's Sparrow detection function

Print method for distance function object

Predict distance functions

simple.expansion

Simple polynomial expansion factors

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

Type of transects

summary.rowwise_df

Summary method for Rdistance data frames

Summarize a distance function object

thrasherDetectionData

Sage Thrasher detection data

Distance function starting values and limits

Sage Thrasher detection data frame in Rdistance >4.0.0 format

Summarize abundance estimates

thrasherSiteData

Sage Thrasher site data.

sparrowSiteData

Brewer's Sparrow site data

Estimate variance-covariance

Unnest an RdistDf data frame

Unit assignment helpers

Effective Detection Radius (EDR) for point transects

Effective Strip Width (ESW) for line transects

Reparameterise Gamma parameters for use in dgamma

Gamma.start.limits

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

Gamma distance function

AIC-related fit statistics for detection functions

Modes of the Gamma distribution

'nlminb' optimizer

'nlminb' optimizer

'optim' optimizer