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secr (version 5.1.0)

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

2,295

Version

5.1.0

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

November 4th, 2024

Functions in secr (5.1.0)

Frequently Asked Questions, And Others

Import or export data

Model Compatibility

Plot Likelihood Surface

Likelihood Ratio Test

Convert Data to RMark Input Format

RSE from Fitted Model

Methods for MCgof Objects

Telemetry Fixes in Polygons

Multi-core Processing

Smoothed Resource Surface

Orongorongo Valley Brushtail Possums

Coerce capthist to Data Frame or Array

Add Binned Covariate

Monte Carlo Goodness-of-fit for SECR Models

Black Bear Hair Snag Dataset

Coerce traps object to mask

Mark-resight Data

Combine Telemetry and Detection Data

Add Covariates to Mask or Traps

Initial Parameter Values for SECR

Spatial Capture History Object

Coerce ppp object to popn

Coefficients of secr Object

Contour Detection Probability

Profile Likelihood Confidence Intervals

Array of Parameter Estimates

Overdispersion of Activity Centres

Circular Probability

Closed population estimates

Dissect Spatial Capture History Object

Deviance of fitted secr model and residual degrees of freedom

Detector Clustering

Derived Parameters of Fitted SECR Model

Deermouse Live-trapping Datasets

Detail Specification for secr.fit

House mouse live trapping data

deleteMaskPoints

Edit Mask Points

Detection Functions

Covariates Attribute

Empirical Variance of H-T Density Estimate

Expected Number of Individuals

Distance To Nearest Detector

Rasterize Area Search or Transect Data

Confidence Ellipses

Construct Grid Cells

Mask Buffer Diagnostic Plot

Activity Centres of Detected and Undetected Animals

First or Last Part of an Object

Probability Density of Activity Centre

Simulated Movements

Home Range Statistics

Hybrid Mixture Model

Multinomial Coefficient of SECR Likelihood

Logit Transformation

Flat-tailed Horned Lizard Dataset

Combine or Split Sessions of capthist Object

Fit Multiple SECR Models

Initial Parameter Values

Work with Open Population data

Construct Spatial Coverage Design

Build Habitat Mask

Construct capthist Object

Construct Lacework Detector Design

Mask Diagnostics

Build Detector Array

make.systematic

Construct Systematic Detector Design

Net Detection Probability

Build Detector Array on Triangular or Hexagonal Grid

Ovenbird Acoustic Dataset

Ovenbird Mist-netting Dataset

Plot Detection Histories

Population Object

Plot Detection Functions

Non-target Data

Plot Habitat Mask, Density or Resource Surface

Plot Population Object

Key to Petal Plot

Averaging of SECR Models Using Akaike's Information Criterion

Create Default Design Data

predictDsurface

Predict Density Surface

Outline Around Mask Cells

Area of Polygon(s)

pointsInPolygon

Points Inside Polygon

Print Detectors

Random Landscape

Brushtail Possum Trapping Dataset

Print Detections

Multi-session Objects

SECR Model Predictions

Create a RasterLayer Object from Mask or Dsurface

Combine capthist Objects

Combine popn Objects

Mixture Model Check

Read Detector Data From File

rectangularMask

Rectangular Mask

Combine traps Objects

Population Size

Score Test for SECR Models

Internal Functions

Plot traps Object

Spatially Explicit Capture--Recapture Models

Import Telemetry Fixes

Defunct Functions in Package secr

Print or Summarise secr Object

secr-deprecated

Deprecated Functions in Package secr

Number of Threads

Construct Detection Model Design Matrices and Lookups

Changes in secr 5.0

shareFactorLevels

Fix Inconsistent Covariates

Goodness-of-fit Test Results

Spatially Explicit Capture--Recapture

Goodness-of-Fit Test

Read Habitat Mask From File

Combine Columns

Sighting Attributes

Reformat Signal Data

Simulate 2-D Population

reduce.capthist

Combine Occasions Or Detectors

Simulate Detection Histories

Slice Transect Into Shorter Sections

Simulate From Fitted secr Model

Subset popn Object

Detector or Mask Spacing

Sort Rows of capthist or mask Object

Colour Strip Legend

Subset traps Object

Mask Buffer Width

summary.capthist

Summarise Detections

Summarise Detector Array

Time-varying Covariates

Random Number Seed

Drop Unwanted List Components

transformations

Transform Point Array

Smooth Terms in SECR Models

SECR Models Fitted to Demonstration Data

Summarise Habitat Mask

Skink Pitfall Data

Subset, Split or Combine Mask Objects

Update Old capthist Format

Summarise Simulated Population

Complex Detector Layouts

Check SECR Data

Non-Euclidean Distances

Detector Attributes

Plot usage, detections or sightings.

Write Data to Text File

Troubleshooting

Problems in Fitting SECR Models

subset.capthist

Subset or Split capthist Object

Specifying a Dynamic Population

Utility Functions

Variance - Covariance Matrix of SECR Parameters

Coefficient of Variation

Density Surfaces

Construct Density Design Data

Convert Data To Or From BUGS Format

Compare SECR Models

Estimate overdispersion