Package index • Distance

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Data preparation

create_bins(): Create bins from a set of binned distances and a set of cutpoints.

create.bins(): Create bins from a set of binned distances and a set of cutpoints.

checkdata(): Check that the data supplied to ds is correct

flatfile: The flatfile data format

Fitting

ds(): Fit detection functions and calculate abundance from line or point transect data

Diagnostics

checkdata(): Check that the data supplied to ds is correct

p_dist_table: Distribution of probabilities of detection

gof_ds(): Goodness of fit testing and quantile-quantile plots

ds.gof(): Goodness of fit tests for distance sampling models

Model selection

AIC(<dsmodel>): Akaike's An Information Criterion for detection functions

logLik(<dsmodel>): log-likelihood value for a fitted detection function

QAIC() chi2_select(): Tools for model selection when distance sampling data are overdispersed

summarize_ds_models(): Make a table of summary statistics for detection function models

Printing and plotting

plot(<dsmodel>): Plot a fitted detection function

add_df_covar_line: Add covariate levels detection function plots

print(<dht_result>): Print abundance estimates

print(<dsmodel>): Simple pretty printer for distance sampling analyses

summary(<dsmodel>): Summary of distance sampling analysis

print(<summary.dsmodel>): Print summary of distance detection function model object

Bootstrap variance estimation

bootdht(): Bootstrap uncertainty estimation for distance sampling models

bootdht_Dhat_summarize(): Simple summary of density results for bootstrap model

bootdht_Nhat_summarize(): Simple summary of abundance results for bootstrap model

make_activity_fn(): Multiplier bootstrap helper functions

summary(<dht_bootstrap>): Summarize bootstrap abundance uncertainty estimate output

Advanced

dht2(): Abundance estimation for distance sampling models

Data sets

amakihi amakihi_units: Hawaiian amakihi point transect data

capercaillie capercaillie_units: Capercaillie in Monaughty Forest

ClusterExercise ClusterExercise_units: Simulated minke whale data with cluster size

CueCountingExample CueCountingExample_units: Cue counts of whale blows

ducknest ducknest_units ducknests_units: Ducknest line transect survey data

DuikerCameraTraps DuikerCameraTraps_units: Duiker camera trap survey

ETP_Dolphin ETP_Dolphin_units: Eastern Tropical Pacific spotted dolphin survey

golftees golftees_units: Golf tee data

LTExercise LTExercise_units: Simulated line transect survey data

minke: Simulated minke whale data

PTExercise PTExercise_units: Simulated point transect survey data

Savannah_sparrow_1980 Savannah_sparrow_1981 Savannah_sparrow_1980_units Savannah_sparrow_1981_units: Savanna sparrow point transects

sikadeer sikadeer_units: Sika deer pellet data from southern Scotland

Stratify_example Stratify_example_units: Simulated minke whale data

Systematic_variance_1 Systematic_variance_2 Systematic_variance_1_units Systematic_variance_2_units: Simulation of encounter rate variance

unimak unimak_units: Simulated line transect survey data with covariates

wren wren_5min wren_snapshot wren_cuecount wren_lt wren_5min_units wren_snapshot_units wren_cuecount_units wren_lt_units: Steve Buckland's winter wren surveys

Miscellaneous

convert_units(): Convert units for abundance estimation

units_table(): Generate table of unit conversions

dummy_ddf(): Detection function objects when detection is certain

predict(<dsmodel>): Predictions from a fitted detection function

predict(<fake_ddf>): Prediction for fake detection functions

unflatten(): Unflatten flatfile data.frames

Distance-package Distance: Distance sampling