Learn R Programming

⚠️There's a newer version (5.2.4) of this package.Take me there.

secr (version 4.4.1)

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.

Copy Link

Version

Install

install.packages('secr')

Monthly Downloads

1,470

Version

4.4.1

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

April 30th, 2021

Functions in secr (4.4.1)

Model Compatibility

Coefficient of Variation

Frequently Asked Questions, And Others

Convert Data To Or From BUGS Format

Construct Density Design Data

Compare SECR Models

Plot Likelihood Surface

Import or export data

Likelihood Ratio Test

Density Surfaces

Add Covariates to Mask or Traps

Mark-resight Data

Telemetry Fixes in Polygons

Orongorongo Valley Brushtail Possums

Multi-core Processing

Convert Data to RMark Input Format

Closed population estimates

Circular Probability

Coerce capthist to Data Frame

Combine Telemetry and Detection Data

Coefficients of secr Object

Detector Clustering

Coerce traps object to mask

Initial Parameter Values for SECR

Dissect Spatial Capture History Object

Spatial Capture History Object

RSE from Fitted Model

Covariates Attribute

Smoothed Resource Surface

House mouse live trapping data

Detection Functions

Deermouse Live-trapping Datasets

deleteMaskPoints

Edit Mask Points

Mask Buffer Diagnostic Plot (internal)

Deviance of fitted secr model and residual degrees of freedom

Confidence Ellipses

Derived Parameters of Fitted SECR Model

Distance To Nearest Detector

Probability Density of Home Range Centre

Activity Centres of Detected and Undetected Animals

Expected Number of Individuals

Combine or Split Sessions of capthist Object

Spatially Explicit Capture--Recapture by Inverse Prediction

Multinomial Coefficient of SECR Likelihood

Logit Transformation

Rasterize Area Search or Transect Data

Flat-tailed Horned Lizard Dataset

Home Range Statistics

Hybrid Mixture Model

Detail Specification for secr.fit

Profile Likelihood Confidence Intervals

First or Last Part of an Object

Empirical Variance of H-T Density Estimate

Multi-session Objects

Key to Petal Plot

Build Habitat Mask

Contour Detection Probability

Mask Buffer Diagnostic Plot

Build Detector Array

make.systematic

Construct Systematic Detector Design

Construct Lacework Detector Design

Construct capthist Object

Work with Open Population data

Net Detection Probability

Fit Multiple SECR Models

Plot Detection Histories

Plot Habitat Mask, Density or Resource Surface

Averaging of SECR Models Using Akaike's Information Criterion

Mask Diagnostics

Plot Detection Functions

Build Detector Array on Triangular or Hexagonal Grid

Plot Population Object

Mixture Model Check

pointsInPolygon

Points Inside Polygon

Combine traps Objects

Read Habitat Mask From File

Brushtail Possum Trapping Dataset

SECR Model Predictions

Plot traps Object

Ovenbird Mist-netting Dataset

Area of Polygon(s)

Ovenbird Acoustic Dataset

Outline Around Mask Cells

predictDsurface

Predict Density Surface

Combine capthist Objects

Population Object

Print Detections

Population Size

reduce.capthist

Combine Occasions Or Detectors

Construct Detection Model Design Matrices and Lookups

Combine popn Objects

Spatially Explicit Capture--Recapture

Create Default Design Data

Goodness-of-Fit Test

Simulate 2-D Population

Simulate From Fitted secr Model

Goodness-of-fit Test Results

Score Test for SECR Models

Read Detector Data From File

Spatially Explicit Capture--Recapture Models

Simulate Detection Histories

Import Telemetry Fixes

Reformat Signal Data

Random Landscape

Sighting Attributes

Detector or Mask Spacing

rectangularMask

Rectangular Mask

Print or Summarise secr Object

Print Detectors

Summarise Detector Array

Combine Columns

Colour Strip Legend

Number of Threads

Subset traps Object

transformations

Transform Point Array

Subset popn Object

Skink Pitfall Data

Smooth Terms in SECR Models

Complex Detector Layouts

Detector Attributes

Variance - Covariance Matrix of SECR Parameters

Plot usage, detections or sightings.

shareFactorLevels

Fix Inconsistent Covariates

Slice Transect Into Shorter Sections

Check SECR Data

Mask Buffer Width

summary.capthist

Summarise Detections

Write Data to Text File

Drop Unwanted List Components

Sort Rows of capthist or mask Object

Troubleshooting

Problems in Fitting SECR Models

Random Number Seed

SECR Models Fitted to Demonstration Data

subset.capthist

Subset or Split capthist Object

Create a RasterLayer Object from Mask or Dsurface

Subset, Split or Combine Mask Objects

Time-varying Covariates

Non-Euclidean Distances

Utility Functions

Summarise Habitat Mask

Specifying a Dynamic Population

Summarise Simulated Population

Update Old capthist Format