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 - PI |
ddf.trial.fi |
Mark-Recapture Analysis of Trial Configuration - FI |
DeltaMethod |
Numeric Delta Method approximation for the variance-covariance matrix |
det.tables |
Observation detection tables |
detfct.fit |
Fit detection function using key-adjustment functions |
detfct.fit.opt |
Fit detection function using key-adjustment functions |
dht |
Density and abundance estimates and variances |
dht.deriv |
Computes abundance estimates at specified parameter values using Horvitz-Thompson-like estimator |
dht.se |
Variance and confidence intervals for density and abundance estimates |
ds.function |
Distance Sampling Functions |
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 |
gof.io |
Goodness of fit tests for distance sampling models |
gof.io.fi |
Goodness of fit tests for distance sampling models |
gof.rem |
Goodness of fit tests for distance sampling models |
gof.rem.fi |
Goodness of fit tests for distance sampling models |
gof.trial |
Goodness of fit tests for distance sampling models |
gof.trial.fi |
Goodness of fit tests for distance sampling models |
gstdint |
Integral of pdf of distances |
p.det |
Double-platform detection probability |
parse.optimx |
Parse optimx results and present a nice object |
pcramer |
Q-Q plot, KS and CVM goodness of fit tests for distance detection functions |
pdot.dsr.integrate.logistic |
Compute probability that a object was detected by at least one observer |
pks |
Q-Q plot, KS and CVM goodness of fit tests for distance detection functions |
plot.det.tables |
Observation detection tables |
plot.ds |
Plot fit of detection functions and histograms of data from distance sampling model |
plot.io |
Plot fit of detection functions and histograms of data from distance sampling independent observer ('io') model |
plot.io.fi |
Plot fit of detection functions and histograms of data from distance sampling independent observer model with full independence ('io.fi') |
plot.layout |
Layout for plot methods in mrds |
plot.rem |
Plot fit of detection functions and histograms of data from removal distance sampling model |
plot.rem.fi |
Plot fit of detection functions and histograms of data from removal distance sampling model |
plot.trial |
Plot fit of detection functions and histograms of data from distance sampling trial observer model |
plot.trial.fi |
Plot fit of detection functions and histograms of data from distance sampling trial observer model |
plot_cond |
Plot conditional detection function from distance sampling model |
plot_uncond |
Plot unconditional detection function from distance sampling model |
predict |
Predictions from 'mrds' models |
predict.ddf |
Predictions from 'mrds' models |
predict.ds |
Predictions from 'mrds' models |
predict.io |
Predictions from 'mrds' models |
predict.io.fi |
Predictions from 'mrds' models |
predict.rem |
Predictions from 'mrds' models |
predict.rem.fi |
Predictions from 'mrds' models |
predict.trial |
Predictions from 'mrds' models |
predict.trial.fi |
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 functions |
print.det.tables |
Print results of observer detection tables |
print.dht |
Prints density and abundance estimates |
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) variance |
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 |
setbounds |
Set parameter bounds |
setcov |
Creates design matrix for covariates in detection function |
sethazard |
Set initial values for detection function based on distance sampling |
setinitial.ds |
Set initial values for detection function based on distance sampling |
sim.mix |
Simulation of distance sampling data via mixture models Allows one to simulate line transect distance sampling data using a mixture of half-normal detection functions. |
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 surveyed region |