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secr (version 5.2.0)

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

2,200

Version

5.2.0

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

January 24th, 2025

Functions in secr (5.2.0)

Frequently Asked Questions, And Others

Likelihood Ratio Test

Smoothed Resource Surface

Multi-core Processing

Telemetry Fixes in Polygons

Convert Data to RMark Input Format

RSE from Fitted Model

Orongorongo Valley Brushtail Possums

Methods for MCgof Objects

Add Covariates to Mask or Traps

Monte Carlo Goodness-of-fit for SECR Models

Spatial Capture History Object

Coerce capthist to Data Frame or Array

Coerce traps object to mask

Coerce ppp object to popn

Add Binned Covariate

Black Bear Hair Snag Dataset

Dissect Spatial Capture History Object

Initial Parameter Values for SECR

Coefficients of secr Object

Array of Parameter Estimates

Profile Likelihood Confidence Intervals

Contour Detection Probability

Closed population estimates

Overdispersion of Activity Centres

Circular Probability

Combine Telemetry and Detection Data

Mark-resight Data

derivedDsurface

Derived Absolute Density

Deermouse Live-trapping Datasets

deleteMaskPoints

Edit Mask Points

Detector Clustering

Covariates Attribute

House mouse live trapping data

Detail Specification for secr.fit

Detection Functions

Derived Parameters of Fitted SECR Model

Deviance of fitted secr model and residual degrees of freedom

Probability Density of Activity Centre

Construct Grid Cells

Confidence Ellipses

Empirical Variance of H-T Density Estimate

Rasterize Area Search or Transect Data

Distance To Nearest Detector

Mask Buffer Diagnostic Plot

Simulated Movements

Activity Centres of Detected and Undetected Animals

Fit Multiple SECR Models

Hybrid Mixture Model

Home Range Statistics

Flat-tailed Horned Lizard Dataset

Expected Number of Individuals

Multinomial Coefficient of SECR Likelihood

Logit Transformation

First or Last Part of an Object

Build Detector Array on Triangular or Hexagonal Grid

Build Detector Array

Create Default Design Data

Combine or Split Sessions of capthist Object

Initial Parameter Values

Work with Open Population data

Construct Spatial Coverage Design

Construct capthist Object

make.systematic

Construct Systematic Detector Design

Key to Petal Plot

Plot Habitat Mask, Density or Resource Surface

Plot Detection Histories

Ovenbird Mist-netting Dataset

Population Object

Area of Polygon(s)

Plot Population Object

Brushtail Possum Trapping Dataset

Plot Detection Functions

Averaging of SECR Models Using Akaike's Information Criterion

SECR Model Predictions

Mask Diagnostics

Multi-session Objects

Non-target Data

Construct Lacework Detector Design

Build Habitat Mask

Mixture Model Check

pointsInPolygon

Points Inside Polygon

Read Habitat Mask From File

Combine traps Objects

Ovenbird Acoustic Dataset

Net Detection Probability

Random Landscape

Print or Summarise secr Object

Combine popn Objects

Combine capthist Objects

Create a RasterLayer Object from Mask or Dsurface

predictDsurface

Predict Density Surface

Print Detectors

Print Detections

Import Telemetry Fixes

reduce.capthist

Combine Occasions Or Detectors

Population Size

rectangularMask

Rectangular Mask

Combine Columns

Plot traps Object

Read Detector Data From File

Defunct Functions in Package secr

Score Test for SECR Models

Outline Around Mask Cells

secr-deprecated

Deprecated Functions in Package secr

Internal Functions

Construct Detection Model Design Matrices and Lookups

Spatially Explicit Capture--Recapture

Changes in secr 5.0

Spatially Explicit Capture--Recapture Models

SECR Models Fitted to Demonstration Data

Goodness-of-fit Test Results

Goodness-of-Fit Test

Random Number Seed

Sighting Attributes

Smooth Terms in SECR Models

Simulate From Fitted secr Model

shareFactorLevels

Fix Inconsistent Covariates

Slice Transect Into Shorter Sections

Simulate Detection Histories

Skink Pitfall Data

Number of Threads

Simulate 2-D Population

Reformat Signal Data

Subset, Split or Combine Mask Objects

Subset popn Object

Subset traps Object

Mask Buffer Width

Colour Strip Legend

Sort Rows of capthist or mask Object

Detector or Mask Spacing

Time-varying Covariates

Detector Attributes

transformations

Transform Point Array

summary.capthist

Summarise Detections

Summarise Simulated Population

Summarise Detector Array

subset.capthist

Subset or Split capthist Object

Drop Unwanted List Components

Summarise Habitat Mask

Troubleshooting

Problems in Fitting SECR Models

Plot usage, detections or sightings.

Write Data to Text File

Specifying a Dynamic Population

Complex Detector Layouts

Non-Euclidean Distances

Utility Functions

Variance - Covariance Matrix of SECR Parameters

Update Old capthist Format

Check SECR Data

Compare SECR Models

Coefficient of Variation

Density Surfaces

Model Compatibility

Estimate overdispersion

Import or export data

Construct Density Design Data

Plot Likelihood Surface

Convert Data To Or From BUGS Format