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Distance

Distance is a simple way of fitting detection functions to distance sampling data for both line and point transects. Adjustment term selection, left and right truncation as well as monotonicity constraints and binning are supported. Abundance and density estimates can also be calculated (via a Horvitz-Thompson-like estimator) if survey area information is provided.

Using Distance

For more information and examples of use take a look at this paper published in Journal of Statistical Software in May 2019.

We also maintain a set of example analyses at examples.distancesampling.org.

Getting Distance

The easiest way to ensure you have the latest version of Distance, is to install Hadley Wickham's devtools package:

  install.packages("devtools")

then install Distance from github:

  library(devtools)
  install_github("DistanceDevelopment/Distance")

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Install

install.packages('Distance')

Monthly Downloads

1,729

Version

1.0.3

License

GPL (>= 2)

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Maintainer

Laura Marshall

Last Published

July 1st, 2021

Functions in Distance (1.0.3)

Savannah_sparrow_1980

Savanna sparrow point transects
DuikerCameraTraps

Duiker camera trap survey
AIC.dsmodel

Akaike's An Information Criterion for detection functions
ClusterExercise

Simulated minke whale data with cluster size
Stratify_example

Simulated minke whale data
CueCountingExample

Cue counts of whale blows
ETP_Dolphin

Eastern Tropical Pacific spotted dolphin survey
PTExercise

Simulated point transect survey data
LTExercise

Simulated line transect survey data
Distance-package

Distance sampling
Systematic_variance_1

Simulation of encounter rate variance
dht2

Abundance estimation for distance sampling models
create.bins

Create bins from a set of binned distances and a set of cutpoints.
bootdht_Nhat_summarize

Simple summary for bootstrap model
capercaillie

Capercaillie in Monaughty Forest
ds.gof

Goodness of fit tests for distance sampling models
ds

Fit detection functions and calculate abundance from line or point transect data
amakihi

Hawaiian amakihi point transect data
bootdht

Bootstrap uncertainty estimation for distance sampling models
print.dht_result

Print abundance estimates
predict.dsmodel

Predictions from a fitted detection function
print.dsmodel

Simple pretty printer for distance sampling analyses
print.summary.dsmodel

Print summary of distance detection function model object
convert_units

Convert units for abundance estimation
summarize_ds_models

Make a table of summary statistics for detection function models
plot.dsmodel

Plot a fitted detection function
checkdata

Check that the data supplied to ds is correct
p_dist_table

Distribution of probabilities of detection
sikadeer

Sika deer pellet data from southern Scotland
flatfile

The flatfile data format
ducknest

Ducknest line transect survey data
gof_ds

Goodness of fit testing and quantile-quantile plots
logLik.dsmodel

log-likelihood value for a fitted detection function
add_df_covar_line

Add covariate levels detection function plots
minke

Simulated minke whale data
unflatten

Unflatten flatfile data.frames
unimak

Simulated line transect survey data with covariates
golftees

Golf tee data
wren

Steve Buckland's winter wren surveys
summary.dht_bootstrap

Summarize bootstrap abundance uncertainty estimate output
units_table

Generate table of unit conversions
summary.dsmodel

Summary of distance sampling analysis