Density and Abundance from Distance-Sampling Surveys

Documentation for package ‘Rdistance’ version 4.1.1

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Rdistance - Distance Sampling Analyses for Abundance Estimation

-- A --

abundEstim	Distance Sampling Abundance Estimates
AIC.dfunc	AIC-related fit statistics for detection functions
autoDistSamp	Automated classical distance analysis

-- B --

bcCI	Bias corrected bootstraps
bspline.expansion	B-spline expansion terms

-- C --

checkNEvalPts	Check number of numeric integration intervals
checkUnits	Check for the presence of units
coef.dfunc	Coefficients of an estimated detection function
colorize	Add color to result if terminal accepts it
control	Rdistance optimization control parameters.
controls	Rdistance optimization control parameters.
cosine.expansion	Cosine expansion terms

-- D --

dE.multi	Estimate multiple-observer line-transect distance functions
dE.single	Estimate single-observer line-transect distance function
dfuncEstim	Estimate a distance-based detection function
dfuncEstimErrMessage	dfuncEstim error messages
differentiableLikelihoods	Differentiable likelihoods in Rdistance
distance	Rdistance - Distance Sampling Analyses for Abundance Estimation
distances	Observation distances
dropUnits	Unit assignment helpers

-- E --

EDR	Effective Detection Radius (EDR) for point transects
effectiveDistance	Effective sampling distances
effort	Effort information
errDataUnk	Unknown error message
estimateN	Abundance point estimates
ESW	Effective Strip Width (ESW) for line transects
expansionTerms	Distance function expansion terms

-- G --

groupSizes	Group Sizes
gxEstim	Estimate g(0) or g(x)

-- H --

halfnorm.like	Half-normal distance function
halfnorm.start.limits	Start and limit values for halfnorm distance function
hazrate.like	Hazard rate likelihood
hazrate.start.limits	Start and limit values for hazrate distance function
hermite.expansion	Hermite expansion factors
HookeJeeves	'nlminb' optimizer

-- I --

insertOneStepBreaks	Insert oneStep Likelihood breaks
integrateHalfnormLines	Integrate Half-normal line surveys
integrateHalfnormPoints	Integrate Half-normal Point transects
integrateHazrateLines	Integrate Hazard-rate line survey distance functions
integrateKey	Compute and print distance function integration
integrateNegexpLines	Integrate Negative exponential
integrateNegexpPoints	Integrate Negative exponential point surveys
integrateNumeric	Numeric Integration
integrateOneStepLines	Integrate Line-transect One-step function
integrateOneStepNumeric	Numeric Integration of One-step Function
integrateOneStepPoints	Integrate Point-survey One-step function
intercept.only	Detect intercept-only distance function
is.points	Tests for point surveys
is.RdistDf	Check RdistDf data frames
is.smoothed	Tests for smoothed distance functions
is.Unitless	Test whether object is unitless

-- L --

likeParamNames	Likelihood parameter names
line-transect	Rdistance - Distance Sampling Analyses for Abundance Estimation
lines.dfunc	lines.dfunc - Line plotting method for distance functions

-- M --

maximize.g	Find coordinate of function maximum
mlEstimates	Distance function maximum likelihood estimates
model.matrix.dfunc	Rdistance model matrix

-- N --

nCovars	Number of covariates
negexp.like	Negative exponential likelihood
negexp.start.limits	Start and limit values for negexp distance function
nLL	Negative log likelihood of distances
Nlminb	'nlminb' optimizer

-- O --

observationType	Type of observations
oneBsIter	Computations for one bootstrap iteration
oneStep.like	Mixture of two uniforms likelihood
oneStep.start.limits	oneStep likelihood start and limit values
Optim	'optim' optimizer

-- P --

parseModel	Parse Rdistance model
perpDists	Compute off-transect distances from sighting distances and angles
plot.dfunc	Plot method for distance (detection) functions
plot.dfunc.para	Plot parametric distance functions
point-transect	Rdistance - Distance Sampling Analyses for Abundance Estimation
predDensity	Density on transects
predDfuncs	Predict distance functions
predict.dfunc	Predict distance functions
predLikelihood	Distance function values at observations
print.abund	Print abundance estimates
print.dfunc	Print method for distance function object

-- R --

Rdistance	Rdistance - Distance Sampling Analyses for Abundance Estimation
RdistanceControls	Rdistance optimization control parameters.
RdistDf	Construct Rdistance nested data frames

-- S --

secondDeriv	Numeric second derivatives
setUnits	Unit assignment helpers
simple.expansion	Simple polynomial expansion factors
simpsonCoefs	Simpson numerical integration coefficients
sine.expansion	Sine expansion terms
sparrowDetectionData	Brewer's Sparrow detection data
sparrowDf	Brewer's Sparrow detection data frame in Rdistance >4.0.0 format.
sparrowDfuncObserver	Brewer's Sparrow detection function
sparrowSiteData	Brewer's Sparrow site data
startLimits	Distance function starting values and limits
summary.abund	Summarize abundance estimates
summary.dfunc	Summarize a distance function object
summary.rowwise_df	Summary method for Rdistance data frames

-- T --

thrasherDetectionData	Sage Thrasher detection data
thrasherDf	Sage Thrasher detection data frame in Rdistance >4.0.0 format
thrasherSiteData	Sage Thrasher site data.
transectType	Type of transects

-- U --

unitHelpers	Unit assignment helpers
unnest	Unnest an RdistDf data frame

-- V --

Estimate variance-covariance

-- misc --