| add.df.covar.line | Add covariate levels detection function plots |
| adj.check.order | Check order of adjustment terms |
| AIC.ddf | Akaike's An Information Criterion for detection functions |
| apex.gamma | Get the apex for a gamma detection function |
| assign.default.values | Assign default values to list elements that have not been... |
| assign.par | Extraction and assignment of parameters to vector |
| average.line | Average detection function line for plotting |
| average.line.cond | Average conditional detection function line for plotting |
| book.tee.data | Golf tee data used in chapter 6 of Advanced Distance Sampling... |
| calc.se.Np | Find se of average p and N |
| cdf.ds | Cumulative distribution function (cdf) for fitted distance... |
| cds | CDS function definition |
| check.bounds | Check parameters bounds during optimisations |
| check.mono | Check that a detection function is monotone |
| coef.ds | Extract coefficients |
| compute.Nht | Horvitz-Thompson estimates 1/p_i or s_i/p_i |
| covered.region.dht | Covered region estimate of abundance from... |
| create.bins | Create bins from a set of binned distances and a set of... |
| create.command.file | create.command.file |
| create.ddfobj | Create detection function object |
| create.model.frame | Create a model frame for ddf fitting |
| create.varstructure | Creates structures needed to compute abundance and variance |
| ddf | Distance Detection Function Fitting |
| ddf.ds | CDS/MCDS Distance Detection Function Fitting |
| ddf.gof | Goodness of fit tests for distance sampling models |
| ddf.io | Mark-Recapture Distance Sampling (MRDS) IO - PI |
| ddf.io.fi | Mark-Recapture Distance Sampling (MRDS) IO - FI |
| ddf.rem | Mark-Recapture Distance Sampling (MRDS) Removal - PI |
| ddf.rem.fi | Mark-Recapture Distance Sampling (MRDS) Removal - FI |
| ddf.trial | Mark-Recapture Distance Sampling (MRDS) Trial Configuration -... |
| ddf.trial.fi | Mark-Recapture Analysis of Trial Configuration - FI |
| DeltaMethod | Numeric Delta Method approximation for the... |
| detfct.fit | Fit detection function using key-adjustment functions |
| detfct.fit.opt | Fit detection function using key-adjustment functions |
| det.tables | Observation detection tables |
| dht | Density and abundance estimates and variances |
| dht.deriv | Computes abundance estimates at specified parameter values... |
| dht.se | Variance and confidence intervals for density and abundance... |
| distpdf | Detection functions |
| ds.function | Distance Sampling Functions |
| flnl | Log-likelihood computation for distance sampling data |
| flt.var | Hessian computation for fitted distance detection function... |
| g0 | Compute value of p(0) using a logit formulation |
| getpar | Extraction and assignment of parameters to vector |
| gof.ds | Compute chi-square goodness-of-fit test for ds models |
| gstdint | Integral of pdf of distances |
| histline | Plot histogram line |
| integratedetfct.logistic | Integrate a logistic detection function |
| integratelogistic.analytic | Analytically integrate logistic detection function |
| integratepdf | Numerically integrate pdf of observed distances over... |
| io.glm | Iterative offset GLM/GAM for fitting detection function |
| is.linear.logistic | Collection of functions for logistic detection functions |
| is.logistic.constant | Is a logit model constant for all observations? |
| keyfct.th1 | Threshold key function |
| keyfct.th2 | Threshold key function |
| keyfct.tpn | Two-part normal key function |
| lfbcvi | Black-capped vireo mark-recapture distance sampling analysis |
| lfgcwa | Golden-cheeked warbler mark-recapture distance sampling... |
| logisticbyx | Logistic as a function of covariates |
| logisticbyz | Logistic as a function of distance |
| logisticdetfct | Logistic detection function |
| logisticdupbyx | Logistic for duplicates as a function of covariates |
| logisticdupbyx_fast | Logistic for duplicates as a function of covariates (fast) |
| logit | Logit function |
| logLik.ddf | log-likelihood value for a fitted detection function |
| mcds | MCDS function definition |
| mcds_dot_exe | Run MCDS.exe as a backend for mrds |
| mrds_opt | Tips on optimisation issues in 'mrds' models |
| mrds-package | Mark-Recapture Distance Sampling (mrds) |
| NCovered | Compute estimated abundance in covered (sampled) region |
| nlminb_wrapper | Wrapper around 'nlminb' |
| parse.optimx | Parse optimx results and present a nice object |
| p.det | Double-platform detection probability |
| p.dist.table | Distribution of probabilities of detection |
| pdot.dsr.integrate.logistic | Compute probability that a object was detected by at least... |
| plot_cond | Plot conditional detection function from distance sampling... |
| plot.det.tables | Observation detection tables |
| plot.ds | Plot fit of detection functions and histograms of data from... |
| plot.io | Plot fit of detection functions and histograms of data from... |
| plot.io.fi | Plot fit of detection functions and histograms of data from... |
| plot_layout | Layout for plot methods in mrds |
| plot.rem | Plot fit of detection functions and histograms of data from... |
| plot.rem.fi | Plot fit of detection functions and histograms of data from... |
| plot.trial | Plot fit of detection functions and histograms of data from... |
| plot.trial.fi | Plot fit of detection functions and histograms of data from... |
| plot_uncond | Plot unconditional detection function from distance sampling... |
| predict.ds | Predictions from 'mrds' models |
| print.ddf | Simple pretty printer for distance sampling analyses |
| print.ddf.gof | Prints results of goodness of fit tests for detection... |
| print.det.tables | Print results of observer detection tables |
| print.dht | Prints density and abundance estimates |
| print.p_dist_table | Print distribution of probabilities of detection |
| print.summary.ds | Print summary of distance detection function model object |
| print.summary.io | Print summary of distance detection function model object |
| print.summary.io.fi | Print summary of distance detection function model object |
| print.summary.rem | Print summary of distance detection function model object |
| print.summary.rem.fi | Print summary of distance detection function model object |
| print.summary.trial | Print summary of distance detection function model object |
| print.summary.trial.fi | Print summary of distance detection function model object |
| prob.deriv | Derivatives for variance of average p and average p(0)... |
| prob.se | Average p and average p(0) variance |
| process.data | Process data for fitting distance sampling detection function |
| pronghorn | Pronghorn aerial survey data from Wyoming |
| ptdata.distance | Single observer point count data example from Distance |
| ptdata.dual | Simulated dual observer point count data |
| ptdata.removal | Simulated removal observer point count data |
| ptdata.single | Simulated single observer point count data |
| qqplot.ddf | Quantile-quantile plot and goodness of fit tests for... |
| rem.glm | Iterative offset model fitting of mark-recapture with removal... |
| rescale_pars | Calculate the parameter rescaling for parameters associated... |
| sample_ddf | Generate data from a fitted detection function and refit the... |
| setbounds | Set parameter bounds |
| setcov | Creates design matrix for covariates in detection function |
| setinitial.ds | Set initial values for detection function based on distance... |
| sim.mix | Simulation of distance sampling data via mixture models... |
| solvecov | Invert of covariance matrices |
| stake77 | Wooden stake data from 1977 survey |
| stake78 | Wooden stake data from 1978 survey |
| summary.ds | Summary of distance detection function model object |
| summary.io | Summary of distance detection function model object |
| summary.io.fi | Summary of distance detection function model object |
| summary.rem | Summary of distance detection function model object |
| summary.rem.fi | Summary of distance detection function model object |
| summary.trial | Summary of distance detection function model object |
| summary.trial.fi | Summary of distance detection function model object |
| survey.region.dht | Extrapolate Horvitz-Thompson abundance estimates to entire... |
| test.breaks | Test validity for histogram breaks(cutpoints) |
| varn | Compute empirical variance of encounter rate |
