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secr (version 5.3.0)

Spatially Explicit Capture-Recapture

Description

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

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Version

Install

install.packages('secr')

Monthly Downloads

1,505

Version

5.3.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/MurrayEfford/secr/

Homepage

https://www.otago.ac.nz/density/

Maintainer

Murray Efford

Last Published

September 27th, 2025

Functions in secr (5.3.0)

Methods for MCgof Objects

Smoothed Resource Surface

Convert Data to RMark Input Format

RSE from Fitted Model

Add Covariates to Mask or Traps

Multi-core Processing

Likelihood Ratio Test

Orongorongo Valley Brushtail Possums

Telemetry Fixes in Polygons

Monte Carlo Goodness-of-fit for SECR Models

Black Bear Hair Snag Dataset

Combine Telemetry and Detection Data

Add Binned Covariate

Mark-resight Data

Coerce ppp object to popn

Spatial Capture History Object

Dissect Spatial Capture History Object

Initial Parameter Values for SECR

Coerce capthist to Data Frame or Array

Coerce traps object to mask

Profile Likelihood Confidence Intervals

Number per detector

Detector Clustering

Closed population estimates

Overdispersion of Activity Centres

Circular Probability

Array of Parameter Estimates

Coefficients of secr Object

Detection Functions

derivedDsurface

Derived Absolute Density

Covariates Attribute

House mouse live trapping data

Contour Detection Probability

deleteMaskPoints

Edit Mask Points

Detail Specification for secr.fit

Derived Parameters of Fitted SECR Model

Deermouse Live-trapping Datasets

Activity Centres of Detected and Undetected Animals

Probability Density of Activity Centre

Rasterize Area Search or Transect Data

Simulated Movements

Confidence Ellipses

Expected Number of Individuals

Mask Buffer Diagnostic Plot

Empirical Variance of H-T Density Estimate

Deviance of fitted secr model and residual degrees of freedom

Distance To Nearest Detector

Construct Grid Cells

Flat-tailed Horned Lizard Dataset

First or Last Part of an Object

Logit Transformation

Multinomial Coefficient of SECR Likelihood

Combine or Split Sessions of capthist Object

Home Range Statistics

Hybrid Mixture Model

Fit Multiple SECR Models

Create Default Design Data

Work with Open Population data

Build Detector Array on Triangular or Hexagonal Grid

Construct capthist Object

Build Habitat Mask

Construct Lacework Detector Design

Construct Spatial Coverage Design

make.systematic

Construct Systematic Detector Design

Initial Parameter Values

Build Detector Array

Averaging of SECR Models Using Akaike's Information Criterion

Non-target Data

Ovenbird Acoustic Dataset

Ovenbird Mist-netting Dataset

Mask Diagnostics

Plot Detection Histories

Multi-session Objects

Net Detection Probability

Key to Petal Plot

Plot Detection Functions

pointsInPolygon

Points Inside Polygon

Area of Polygon(s)

Plot Population Object

Outline Around Mask Cells

Brushtail Possum Trapping Dataset

Plot traps Object

Population Object

Plot Habitat Mask, Density or Resource Surface

Random Landscape

Mixture Model Check

Print Detectors

Create a RasterLayer Object from Mask or Dsurface

Combine popn Objects

Print Detections

predictDsurface

Predict Density Surface

SECR Model Predictions

Combine traps Objects

Combine capthist Objects

Print or Summarise secr Object

Combine Columns

Read Detector Data From File

Population Size

Defunct Functions in Package secr

secr-deprecated

Deprecated Functions in Package secr

Score Test for SECR Models

reduce.capthist

Combine Occasions Or Detectors

rectangularMask

Rectangular Mask

Read Habitat Mask From File

Import Telemetry Fixes

Repeat or Resume Model Fit

Goodness-of-fit Test Results

SECR Models Fitted to Demonstration Data

Changes in secr 5.0

Construct Detection Model Design Matrices and Lookups

Spatially Explicit Capture--Recapture

Internal Functions

Spatially Explicit Capture--Recapture Models

Random Number Seed

Goodness-of-Fit Test

Simulate Detection Histories

Reformat Signal Data

shareFactorLevels

Fix Inconsistent Covariates

Simulate Detections For Ornstein-Uhlenbeck Movement

Simulate 2-D Population

Simulate From Fitted secr Model

Sighting Attributes

Number of Threads

Slice Transect Into Shorter Sections

subset.capthist

Subset or Split capthist Object

Detector or Mask Spacing

Subset, Split or Combine Mask Objects

Colour Strip Legend

Skink Pitfall Data

Smooth Terms in SECR Models

Summarise Detector Array

Summarise Habitat Mask

transformations

Transform Point Array

Sort Rows of capthist or mask Object

Subset popn Object

summary.capthist

Summarise Detections

Mask Buffer Width

Summarise Simulated Population

Specifying a Dynamic Population

Plot usage, detections or sightings.

Complex Detector Layouts

Troubleshooting

Problems in Fitting SECR Models

Drop Unwanted List Components

Time-varying Covariates

Subset traps Object

Detector Attributes

Check SECR Data

Write Data to Text File

Non-Euclidean Distances

Update Old capthist Format

Utility Functions

Variance - Covariance Matrix of SECR Parameters

Convert Data To Or From BUGS Format

Import or export data

Model Compatibility

Construct Density Design Data

Estimate overdispersion

Frequently Asked Questions, And Others

Coefficient of Variation

Density Surfaces

Compare SECR Models

Plot Likelihood Surface