Package: Rdistance 4.0.3

Rdistance: Density and Abundance from Distance-Sampling Surveys

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.

Authors:Trent McDonald [cre, aut], Jason Carlisle [aut], Aidan McDonald [aut], Ryan Nielson [ctb], Ben Augustine [ctb], James Griswald [ctb], Patrick McKann [ctb], Lacey Jeroue [ctb], Hoffman Abigail [ctb], Kleinsausser Michael [ctb], Joel Reynolds [ctb], Pham Quang [ctb], Earl Becker [ctb], Aaron Christ [ctb], Brook Russelland [ctb], Stefan Emmons [ctb], Will McDonald [ctb], Reid Olson [ctb]

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Rdistance.pdf |Rdistance.html
Rdistance/json (API)
NEWS

# Install 'Rdistance' in R:
install.packages('Rdistance', repos = c('https://tmcd82070.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tmcd82070/rdistance/issues

Datasets:

On CRAN:

Conda:

5.56 score 9 stars 40 scripts 476 downloads 1 mentions 44 exports 27 dependencies

Last updated 6 hours agofrom:e2c02964a8. Checks:4 OK, 5 NOTE. Indexed: yes.

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Doc / VignettesOKApr 01 2025
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R-4.5-linuxOKApr 01 2025
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R-4.4-linuxNOTEApr 01 2025
R-4.3-winNOTEApr 01 2025
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Exports:abundEstimautoDistSampbcCIcheckUnitscosine.expansiondE.multidE.singledfuncEstimdistancesEDReffectiveDistanceeffortestimateNESWexpansionTermsgroupSizesgxEstimhalfnorm.likehalfnorm.start.limitshazrate.likehazrate.start.limitshermite.expansionis.pointsis.RdistDfis.smoothedis.UnitlesslikeParamNamesmaximize.gmlEstimatesnegexp.likenegexp.start.limitsnLLobservationTypeparseModelperpDistspredDensitypredDfuncspredLikelihoodRdistDfsecondDerivsimple.expansionstartLimitstransectTypeunnest

Dependencies:clicpp11crayondplyrfansigenericsgluehmslifecyclemagrittrpillarpkgconfigprettyunitsprogresspurrrR6Rcpprlangstringistringrtibbletidyrtidyselectunitsutf8vctrswithr

Readme and manuals

Help Manual

Help pageTopics
Rdistance - Distance Sampling Analyses for Abundance EstimationRdistance-package distance line-transect point-transect Rdistance
abundEstim - Distance Sampling Abundance EstimatesabundEstim
AIC.dfunc - AIC-related fit statistics for detection functionsAIC.dfunc
autoDistSamp - Automated classical distance analysisautoDistSamp
bcCI - Bias corrected bootstrapsbcCI
checkNEvalPts - Check number of numeric integration intervalscheckNEvalPts
checkUnits - Check for the presence of unitscheckUnits
coef.dfunc - Coefficients of an estimated detection functioncoef.dfunc
colorize - Add color to result if terminal accepts itcolorize
cosine.expansion - Cosine expansion termscosine.expansion
dE.multi - Estimate multiple-observer line-transect distance functionsdE.multi
dE.single - Estimate single-observer line-transect distance functiondE.single
dfuncEstim - Estimate a distance-based detection functiondfuncEstim
dfuncEstimErrMessage - dfuncEstim error messagesdfuncEstimErrMessage
distances - Observation distancesdistances
EDR - Effective Detection Radius (EDR) for point transectsEDR
effectiveDistance - Effective sampling distanceseffectiveDistance
effort - Effort informationeffort
errDataUnk - Unknown error messageerrDataUnk
estimateN - Abundance point estimatesestimateN
ESW - Effective Strip Width (ESW) for line transectsESW
expansionTerms - Distance function expansion termsexpansionTerms
groupSizes - Group SizesgroupSizes
gxEstim - Estimate g(0) or g(x)gxEstim
halfnorm.like - Half-normal distance functionhalfnorm.like
halfnorm.start.limits - Start and limit values for halfnorm distance functionhalfnorm.start.limits
hazrate.like - Hazard rate likelihoodhazrate.like
hazrate.start.limits - Start and limit values for hazrate distance functionhazrate.start.limits
Calculation of Hermite expansion for detection function likelihoodshermite.expansion
intercept.only - Detect intercept-only distance functionintercept.only
is.points - Tests for point surveysis.points
checkRdistDf - Check RdistDf data framesis.RdistDf
is.smoothed - Tests for smoothed distance functionsis.smoothed
is.Unitless - Test whether object is unitlessis.Unitless
Likelihood parameter nameslikeParamNames
lines.dfunc - Line plotting method for distance functionslines.dfunc
maximize.g - Find coordinate of function maximummaximize.g
mlEstimates - Distance function maximum likelihood estimatesmlEstimates
model.matrix - Rdistance model matrixmodel.matrix.dfunc
nCovars - Number of covariatesnCovars
negexp.like - Negative exponential likelihoodnegexp.like
negexp.start.limits - Start and limit values for negexp distance functionnegexp.start.limits
nLL - Negative log likelihood of distancesnLL
observationType - Type of observationsobservationType
oneBsIter - Computations for one bootstrap iterationoneBsIter
parseModel - Parse Rdistance modelparseModel
Compute off-transect distances from sighting distances and anglesperpDists
plot.dfunc - Plot method for distance (detection) functionsplot.dfunc
plot.dfunc.para - Plot parametric distance functionsplot.dfunc.para
predDensity - Density on transectspredDensity
predDfuncs - Predict distance functionspredDfuncs
predict.dfunc - Predict distance functionspredict.dfunc
predLikelihood - Distance function values at observationspredLikelihood
Print abundance estimatesprint.abund
print.dfunc - Print method for distance function objectprint.dfunc
Rdistance optimization control parameters.control controls RdistanceControls
RdistDf - Construct Rdistance nested data framesRdistDf
Numeric second derivativessecondDeriv
Calculate simple polynomial expansion for detection function likelihoodssimple.expansion
Brewer's Sparrow detection datasparrowDetectionData
Brewer's Sparrow detection data frame in Rdistance >4.0.0 format.sparrowDf
Brewer's Sparrow detection functionsparrowDfuncObserver
Brewer's Sparrow site datasparrowSiteData
startLimits - Distance function starting values and limitsstartLimits
Summarize abundance estimatessummary.abund
Summarize a distance function objectsummary.dfunc
summary.rowwise_df - Summary method for Rdistance data framessummary.rowwise_df
Sage Thrasher detection datathrasherDetectionData
Sage Thrasher detection data frame in Rdistance >4.0.0 formatthrasherDf
thrasherSiteData - Sage Thrasher site data.thrasherSiteData
transectType - Type of transectstransectType
unnest - Unnest an RdistDf data frameunnest