Man pages for Rdistance
Density and Abundance from Distance-Sampling Surveys
| abundEstim | Distance Sampling Abundance Estimates |
| AIC.dfunc | AIC-related fit statistics for detection functions |
| autoDistSamp | Automated classical distance analysis |
| bcCI | Bias corrected bootstraps |
| bootstrap | Perform bootstrap iterations |
| bspline.expansion | B-spline expansion terms |
| 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 |
| cosine.expansion | Cosine expansion terms |
| 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 |
| distances | Observation distances |
| 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 |
| Gamma.like | Gamma distance function |
| GammaModes | Modes of the Gamma distribution |
| GammaReparam | Reparameterise Gamma parameters for use in dgamma |
| Gamma.start.limits | Gamma.start.limits - Start and limit values for Gamma... |
| getNCores | Set number of cores |
| groupSizes | Group Sizes |
| gxEstim | Estimate g(0) or g(x) |
| 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 |
| insertOneStepBreaks | Insert oneStep Likelihood breaks |
| integrateDfuncs | Integration of distance functions |
| 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 |
| 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 |
| likeParamNames | Likelihood parameter names |
| lines.dfunc | lines.dfunc - Line plotting method for distance functions |
| maximize.g | Find coordinate of function maximum |
| mlEstimates | Distance function maximum likelihood estimates |
| model.matrix.dfunc | Rdistance model matrix |
| 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 |
| observationType | Type of observations |
| oneBsIter | Calculations for one bootstrap iteration |
| oneStep.like | Mixture of two uniforms likelihood |
| oneStep.start.limits | oneStep likelihood start and limit values |
| Optim | 'optim' optimizer |
| parseModel | Parse Rdistance model |
| perpDists | Compute off-transect distances from sighting distances and... |
| plot.dfunc | Plot method for distance (detection) functions |
| plot.dfunc.para | Plot parametric distance functions |
| 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 |
| RdistanceControls | Rdistance optimization control parameters. |
| Rdistance-package | Rdistance - Distance Sampling Analyses for Abundance... |
| RdistDf | Construct Rdistance nested data frames |
| secondDeriv | Numeric second derivatives |
| 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... |
| 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 |
| 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 |
| unitHelpers | Unit assignment helpers |
| unnest | Unnest an RdistDf data frame |
| varcovarEstim | Estimate variance-covariance |
