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Rdistance (version 4.0.5)

Density and Abundance from Distance-Sampling Surveys

Description

Distance-sampling () 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.

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install.packages('Rdistance')

Monthly Downloads

483

Version

4.0.5

License

GNU General Public License

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Maintainer

Trent McDonald

Last Published

April 10th, 2025

Functions in Rdistance (4.0.5)

dE.multi

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

dfuncEstimErrMessage - dfuncEstim error messages
dfuncEstim

dfuncEstim - Estimate a distance-based detection function
distances

distances - Observation distances
checkUnits

checkUnits - Check for the presence of units
colorize

colorize - Add color to result if terminal accepts it
effectiveDistance

effectiveDistance - Effective sampling distances
dE.single

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

coef.dfunc - Coefficients of an estimated detection function
cosine.expansion

cosine.expansion - Cosine expansion terms
groupSizes

groupSizes - Group Sizes
errDataUnk

errDataUnk - Unknown error message
hazrate.like

hazrate.like - Hazard rate likelihood
expansionTerms

expansionTerms - Distance function expansion terms
halfnorm.start.limits

halfnorm.start.limits - Start and limit values for halfnorm distance function
effort

effort - Effort information
halfnorm.like

halfnorm.like - Half-normal distance function
hazrate.start.limits

hazrate.start.limits - Start and limit values for hazrate distance function
estimateN

estimateN - Abundance point estimates
is.RdistDf

checkRdistDf - Check RdistDf data frames
gxEstim

gxEstim - Estimate g(0) or g(x)
intercept.only

intercept.only - Detect intercept-only distance function
is.points

is.points - Tests for point surveys
hermite.expansion

Calculation of Hermite expansion for detection function likelihoods
is.smoothed

is.smoothed - Tests for smoothed distance functions
maximize.g

maximize.g - Find coordinate of function maximum
mlEstimates

mlEstimates - Distance function maximum likelihood estimates
is.Unitless

is.Unitless - Test whether object is unitless
perpDists

Compute off-transect distances from sighting distances and angles
plot.dfunc

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

parseModel - Parse Rdistance model
oneBsIter

oneBsIter - Computations for one bootstrap iteration
model.matrix.dfunc

model.matrix - Rdistance model matrix
print.abund

Print abundance estimates
predict.dfunc

predict.dfunc - Predict distance functions
nCovars

nCovars - Number of covariates
print.dfunc

print.dfunc - Print method for distance function object
secondDeriv

Numeric second derivatives
sparrowDetectionData

Brewer's Sparrow detection data
simple.expansion

Calculate simple polynomial expansion for detection function likelihoods
thrasherDf

Sage Thrasher detection data frame in Rdistance >4.0.0 format
summary.rowwise_df

summary.rowwise_df - Summary method for Rdistance data frames
thrasherDetectionData

Sage Thrasher detection data
thrasherSiteData

thrasherSiteData - Sage Thrasher site data.
sparrowDfuncObserver

Brewer's Sparrow detection function
negexp.like

negexp.like - Negative exponential likelihood
predLikelihood

predLikelihood - Distance function values at observations
sparrowDf

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

predDfuncs - Predict distance functions
transectType

transectType - Type of transects
unnest

unnest - Unnest an RdistDf data frame
summary.dfunc

Summarize a distance function object
summary.abund

Summarize abundance estimates
nLL

nLL - Negative log likelihood of distances
lines.dfunc

lines.dfunc - Line plotting method for distance functions
negexp.start.limits

negexp.start.limits - Start and limit values for negexp distance function
plot.dfunc.para

plot.dfunc.para - Plot parametric distance functions
likeParamNames

Likelihood parameter names
observationType

observationType - Type of observations
predDensity

predDensity - Density on transects
sparrowSiteData

Brewer's Sparrow site data
startLimits

startLimits - Distance function starting values and limits
checkNEvalPts

checkNEvalPts - Check number of numeric integration intervals
ESW

ESW - Effective Strip Width (ESW) for line transects
Rdistance-package

Rdistance - Distance Sampling Analyses for Abundance Estimation
RdistanceControls

Rdistance optimization control parameters.
bcCI

bcCI - Bias corrected bootstraps
RdistDf

RdistDf - Construct Rdistance nested data frames
abundEstim

abundEstim - Distance Sampling Abundance Estimates
EDR

EDR - Effective Detection Radius (EDR) for point transects
AIC.dfunc

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

autoDistSamp - Automated classical distance analysis