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secr (version 4.6.1)

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

1,470

Version

4.6.1

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

July 10th, 2023

Functions in secr (4.6.1)

Model Compatibility

Convert Data To Or From BUGS Format

Compare SECR Models

Density Surfaces

Estimate overdispersion

Construct Density Design Data

Coefficient of Variation

Import or export data

Frequently Asked Questions, And Others

Plot Likelihood Surface

Mark-resight Data

Multi-core Processing

Telemetry Fixes in Polygons

Convert Data to RMark Input Format

Smoothed Resource Surface

Likelihood Ratio Test

Add Covariates to Mask or Traps

Combine Telemetry and Detection Data

Orongorongo Valley Brushtail Possums

RSE from Fitted Model

Coerce capthist to Data Frame

Initial Parameter Values for SECR

Circular Probability

Closed population estimates

Spatial Capture History Object

Coerce traps object to mask

Contour Detection Probability

Covariates Attribute

House mouse live trapping data

Dissect Spatial Capture History Object

Detector Clustering

Array of Parameter Estimates

Deermouse Live-trapping Datasets

Profile Likelihood Confidence Intervals

Coefficients of secr Object

deleteMaskPoints

Edit Mask Points

Mask Buffer Diagnostic Plot

Rasterize Area Search or Transect Data

Overdispersion of Activity Centres

Mask Buffer Diagnostic Plot (internal)

Derived Parameters of Fitted SECR Model

Deviance of fitted secr model and residual degrees of freedom

Detail Specification for secr.fit

Confidence Ellipses

Detection Functions

Distance To Nearest Detector

Empirical Variance of H-T Density Estimate

Construct Grid Cells

Home Range Statistics

First or Last Part of an Object

Activity Centres of Detected and Undetected Animals

Probability Density of Home Range Centre

Expected Number of Individuals

Simulated Movements

Flat-tailed Horned Lizard Dataset

Combine or Split Sessions of capthist Object

Hybrid Mixture Model

Build Habitat Mask

make.systematic

Construct Systematic Detector Design

Initial Parameter Values

Construct capthist Object

Construct Lacework Detector Design

Logit Transformation

Work with Open Population data

Build Detector Array

model.average-deprecated

Old Model Average Function

Key to Petal Plot

Multi-session Objects

Build Detector Array on Triangular or Hexagonal Grid

Ovenbird Mist-netting Dataset

Averaging of SECR Models Using Akaike's Information Criterion

Multinomial Coefficient of SECR Likelihood

Non-target Data

Ovenbird Acoustic Dataset

Fit Multiple SECR Models

Plot traps Object

Plot Detection Functions

pointsInPolygon

Points Inside Polygon

Mask Diagnostics

Outline Around Mask Cells

Mixture Model Check

Net Detection Probability

Plot Habitat Mask, Density or Resource Surface

Plot Detection Histories

Area of Polygon(s)

SECR Model Predictions

Create a RasterLayer Object from Mask or Dsurface

Plot Population Object

Brushtail Possum Trapping Dataset

Combine capthist Objects

Population Object

predictDsurface

Predict Density Surface

Print Detections

Read Habitat Mask From File

Combine popn Objects

Import Telemetry Fixes

Print Detectors

Print or Summarise secr Object

Read Detector Data From File

Combine traps Objects

Population Size

Score Test for SECR Models

Random Landscape

Combine Columns

rectangularMask

Rectangular Mask

Defunct Functions in Package secr

Create Default Design Data

secr-deprecated

Deprecated Functions in Package secr

reduce.capthist

Combine Occasions Or Detectors

Random Number Seed

Goodness-of-Fit Test

Construct Detection Model Design Matrices and Lookups

SECR Models Fitted to Demonstration Data

Spatially Explicit Capture--Recapture

Internal Functions

Spatially Explicit Capture--Recapture Models

Number of Threads

Reformat Signal Data

Goodness-of-fit Test Results

shareFactorLevels

Fix Inconsistent Covariates

Sighting Attributes

Simulate Detection Histories

Simulate 2-D Population

Skink Pitfall Data

Simulate From Fitted secr Model

Slice Transect Into Shorter Sections

Detector or Mask Spacing

subset.capthist

Subset or Split capthist Object

Smooth Terms in SECR Models

Subset, Split or Combine Mask Objects

Colour Strip Legend

Sort Rows of capthist or mask Object

transformations

Transform Point Array

Summarise Detector Array

Summarise Habitat Mask

Complex Detector Layouts

summary.capthist

Summarise Detections

Subset traps Object

Subset popn Object

Mask Buffer Width

Time-varying Covariates

Summarise Simulated Population

Plot usage, detections or sightings.

Troubleshooting

Problems in Fitting SECR Models

Specifying a Dynamic Population

Drop Unwanted List Components

Detector Attributes

Non-Euclidean Distances

Update Old capthist Format

Write Data to Text File

Utility Functions

Variance - Covariance Matrix of SECR Parameters

Check SECR Data