Rdistance4.0.3 package

Density and Abundance from Distance-Sampling Surveys

hazrate.start.limits

hazrate.start.limits - Start and limit values for hazrate distance fun...

hermite.expansion

Calculation of Hermite expansion for detection function likelihoods

intercept.only

intercept.only - Detect intercept-only distance function

is.points

is.points - Tests for point surveys

isistDf.Rd

checkRdistDf - Check RdistDf data frames

is.smoothed

is.smoothed - Tests for smoothed distance functions

is.Unitless

is.Unitless - Test whether object is unitless

likeParamNames

Likelihood parameter names

abundEstim

abundEstim - Distance Sampling Abundance Estimates

AIC.dfunc

AIC.dfunc - AIC-related fit statistics for detection functions

autoDistSamp

autoDistSamp - Automated classical distance analysis

bcCI

bcCI - Bias corrected bootstraps

checkNEvalPts

checkNEvalPts - Check number of numeric integration intervals

checkUnits

checkUnits - Check for the presence of units

coef.dfunc

coef.dfunc - Coefficients of an estimated detection function

colorize

colorize - Add color to result if terminal accepts it

cosine.expansion

cosine.expansion - Cosine expansion terms

dE.multi

dE.multi - Estimate multiple-observer line-transect distance functions

dE.single

dE.single - Estimate single-observer line-transect distance function

dfuncEstim

dfuncEstim - Estimate a distance-based detection function

dfuncEstimErrMessage

dfuncEstimErrMessage - dfuncEstim error messages

distances

distances - Observation distances

EDR

EDR - Effective Detection Radius (EDR) for point transects

effectiveDistance

effectiveDistance - Effective sampling distances

effort

effort - Effort information

errDataUnk

errDataUnk - Unknown error message

estimateN

estimateN - Abundance point estimates

ESW

ESW - Effective Strip Width (ESW) for line transects

expansionTerms

expansionTerms - Distance function expansion terms

groupSizes

groupSizes - Group Sizes

gxEstim

gxEstim - Estimate g(0) or g(x)

halfnorm.like

halfnorm.like - Half-normal distance function

halfnorm.start.limits

halfnorm.start.limits - Start and limit values for halfnorm distance f...

hazrate.like

hazrate.like - Hazard rate likelihood

lines.dfunc

lines.dfunc - Line plotting method for distance functions

maximize.g

maximize.g - Find coordinate of function maximum

mlEstimates

mlEstimates - Distance function maximum likelihood estimates

model.matrix.dfunc

model.matrix - Rdistance model matrix

nCovars

nCovars - Number of covariates

negexp.like

negexp.like - Negative exponential likelihood

negexp.start.limits

negexp.start.limits - Start and limit values for negexp distance funct...

nLL

nLL - Negative log likelihood of distances

observationType

observationType - Type of observations

oneBsIter

oneBsIter - Computations for one bootstrap iteration

parseModel

parseModel - Parse Rdistance model

perpDists

Compute off-transect distances from sighting distances and angles

plot.dfunc.para

plot.dfunc.para - Plot parametric distance functions

plot.dfunc

plot.dfunc - Plot method for distance (detection) functions

predDensity

predDensity - Density on transects

predDfuncs

predDfuncs - Predict distance functions

predict.dfunc

predict.dfunc - Predict distance functions

predLikelihood

predLikelihood - Distance function values at observations

print.abund

Print abundance estimates

print.dfunc

print.dfunc - Print method for distance function object

Rdistance-package

Rdistance - Distance Sampling Analyses for Abundance Estimation

RdistanceControls

Rdistance optimization control parameters.

RdistDf

RdistDf - Construct Rdistance nested data frames

secondDeriv

Numeric second derivatives

simple.expansion

Calculate simple polynomial expansion for detection function likelihoo...

startLimits

startLimits - Distance function starting values and limits

summary.abund

Summarize abundance estimates

summary.dfunc

Summarize a distance function object

summary.rowwise_df

summary.rowwise_df - Summary method for Rdistance data frames

transectType

transectType - Type of transects

unnest

unnest - Unnest an RdistDf data frame

Distance-sampling (<doi:10.1007/978-3-319-19219-2>) estimates density and abundance of survey targets (e.g., animals) when detection probability declines with 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. Distance-sampling includes line-transect studies that measure observation distances as the closest approach of the sample route (transect) to the target (i.e., perpendicular off-transect distance), and point-transect studies that measure observation distances from stationary observers to the target (i.e., radial distance). The routines included here fit smooth (parametric) curves to histograms of observation distances and use those functions to compute effective sampling distances, density of targets in the surveyed area, and abundance of targets in a surrounding study area. Curve shapes include the half-normal, hazard rate, and negative exponential functions. Physical measurement units are required and used throughout to ensure density is reported correctly. The help files are extensive and have been vetted by multiple authors.

  • Maintainer: Trent McDonald
  • License: GNU General Public License
  • Last published: 2025-03-29