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secr (version 5.0.0)

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

2,124

Version

5.0.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

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

Homepage

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

Maintainer

Last Published

October 2nd, 2024

Functions in secr (5.0.0)

Smoothed Resource Surface

Telemetry Fixes in Polygons

Methods for MCgof Objects

Likelihood Ratio Test

Convert Data to RMark Input Format

Orongorongo Valley Brushtail Possums

Monte Carlo Goodness-of-fit for SECR Models

Multi-core Processing

Add Covariates to Mask or Traps

RSE from Fitted Model

Spatial Capture History Object

Mark-resight Data

Black Bear Hair Snag Dataset

Coerce traps object to mask

Coerce capthist to Data Frame or Array

Add Binned Covariate

Initial Parameter Values for SECR

Coerce ppp object to popn

Combine Telemetry and Detection Data

Dissect Spatial Capture History Object

Contour Detection Probability

Profile Likelihood Confidence Intervals

Circular Probability

Detector Clustering

Coefficients of secr Object

Array of Parameter Estimates

Overdispersion of Activity Centres

Closed population estimates

Deviance of fitted secr model and residual degrees of freedom

Deermouse Live-trapping Datasets

Detection Functions

House mouse live trapping data

Detail Specification for secr.fit

Derived Parameters of Fitted SECR Model

deleteMaskPoints

Edit Mask Points

Rasterize Area Search or Transect Data

Covariates Attribute

Empirical Variance of H-T Density Estimate

Expected Number of Individuals

Construct Grid Cells

Activity Centres of Detected and Undetected Animals

Distance To Nearest Detector

Confidence Ellipses

Simulated Movements

Hybrid Mixture Model

Mask Buffer Diagnostic Plot

Fit Multiple SECR Models

Flat-tailed Horned Lizard Dataset

Probability Density of Activity Centre

Combine or Split Sessions of capthist Object

Home Range Statistics

First or Last Part of an Object

Logit Transformation

Multinomial Coefficient of SECR Likelihood

Construct capthist Object

Construct Lacework Detector Design

Initial Parameter Values

make.systematic

Construct Systematic Detector Design

Construct Spatial Coverage Design

Build Habitat Mask

Build Detector Array on Triangular or Hexagonal Grid

Create Default Design Data

Mask Diagnostics

Work with Open Population data

Build Detector Array

Net Detection Probability

Plot Detection Histories

Non-target Data

Ovenbird Acoustic Dataset

Ovenbird Mist-netting Dataset

Plot Habitat Mask, Density or Resource Surface

Plot Population Object

Key to Petal Plot

Plot Detection Functions

Plot traps Object

Brushtail Possum Trapping Dataset

Population Object

SECR Model Predictions

predictDsurface

Predict Density Surface

Outline Around Mask Cells

Create a RasterLayer Object from Mask or Dsurface

Mixture Model Check

Combine popn Objects

Combine traps Objects

Print Detections

Print or Summarise secr Object

Import Telemetry Fixes

Read Habitat Mask From File

Combine capthist Objects

Defunct Functions in Package secr

Population Size

Read Detector Data From File

secr-deprecated

Deprecated Functions in Package secr

Internal Functions

pointsInPolygon

Points Inside Polygon

Multi-session Objects

Print Detectors

Random Landscape

Averaging of SECR Models Using Akaike's Information Criterion

Area of Polygon(s)

reduce.capthist

Combine Occasions Or Detectors

Combine Columns

rectangularMask

Rectangular Mask

Spatially Explicit Capture--Recapture Models

Number of Threads

Score Test for SECR Models

Changes in secr 5.0

Construct Detection Model Design Matrices and Lookups

Goodness-of-fit Test Results

Random Number Seed

SECR Models Fitted to Demonstration Data

Spatially Explicit Capture--Recapture

Goodness-of-Fit Test

shareFactorLevels

Fix Inconsistent Covariates

Skink Pitfall Data

Smooth Terms in SECR Models

Sighting Attributes

Reformat Signal Data

Simulate Detection Histories

Simulate 2-D Population

Simulate From Fitted secr Model

Slice Transect Into Shorter Sections

Sort Rows of capthist or mask Object

Subset traps Object

Subset popn Object

Mask Buffer Width

summary.capthist

Summarise Detections

Subset, Split or Combine Mask Objects

subset.capthist

Subset or Split capthist Object

Detector or Mask Spacing

Detector Attributes

transformations

Transform Point Array

Time-varying Covariates

Summarise Detector Array

Summarise Simulated Population

Summarise Habitat Mask

Complex Detector Layouts

Drop Unwanted List Components

Colour Strip Legend

Check SECR Data

Plot usage, detections or sightings.

Non-Euclidean Distances

Write Data to Text File

Update Old capthist Format

Utility Functions

Variance - Covariance Matrix of SECR Parameters

Troubleshooting

Problems in Fitting SECR Models

Specifying a Dynamic Population

Convert Data To Or From BUGS Format

Estimate overdispersion

Frequently Asked Questions, And Others

Compare SECR Models

Import or export data

Coefficient of Variation

Density Surfaces

Construct Density Design Data

Plot Likelihood Surface

Model Compatibility