Learn R Programming

⚠️There's a newer version (5.2.1) of this package.Take me there.

secr (version 3.2.1)

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

2,295

Version

3.2.1

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

June 3rd, 2019

Functions in secr (3.2.1)

Import or export data

Frequently Asked Questions, And Others

Density Surfaces

Orongorongo Valley Brushtail Possums

Likelihood Ratio Test

Coefficient of Variation

Plot Likelihood Surface

Construct Density Design Data

Convert Data To Or From BUGS Format

Compare SECR Models

Exchange data with SPACECAP package

Mark-resight Data

Telemetry Fixes in Polygons

Multi-core Processing

Coerce traps object to mask

Coerce capthist to Data Frame

Smoothed Resource Surface

Convert Data to RMark Input Format

Add Covariates to Mask or Traps

Closed population estimates

Coefficients of secr Object

Profile Likelihood Confidence Intervals

Combine Telemetry and Detection Data

Dissect Spatial Capture History Object

Initial Parameter Values for SECR

Circular Probability

Spatial Capture History Object

Detail Specification for secr.fit

deleteMaskPoints

Edit Mask Points

Deviance of fitted secr model and residual degrees of freedom

Detector Clustering

Expected Number of Individuals

Activity Centres of Detected and Undetected Animals

Detection Functions

Hybrid Mixture Model

Probability Density of Home Range Centre

Derived Parameters of Fitted SECR Model

Confidence Ellipses

Covariates Attribute

Deermouse Live-trapping Datasets

Build Habitat Mask

make.systematic

Construct Systematic Detector Design

Contour Detection Probability

Mask Buffer Diagnostic Plot (internal)

Mask Buffer Diagnostic Plot

House mouse live trapping data

Empirical Variance of H-T Density Estimate

Rasterize Area Search or Transect Data

Distance To Nearest Detector

Multi-session Objects

Key to Petal Plot

Construct capthist Object

Multinomial Coefficient of SECR Likelihood

Logit Transformation

Ovenbird Acoustic Dataset

Ovenbird Mist-netting Dataset

Combine or Split Sessions of capthist Object

Build Detector Array

Flat-tailed Horned Lizard Dataset

Home Range Statistics

Work with Open Population data

First or Last Part of an Object

Plot popn Object

Plot Detection Functions

Build Detector Array on Triangular or Hexagonal Grid

Fit Multiple SECR Models

Mask Diagnostics

Spatially Explicit Capture--Recapture by Inverse Prediction

Averaging of SECR Models Using Akaike's Information Criterion

Net Detection Probability

Plot Detection Histories

Plot Habitat Mask, Density or Resource Surface

Brushtail Possum Trapping Dataset

SECR Model Predictions

Random Landscape

reduce.capthist

Combine Occasions Or Detectors

Create a RasterLayer Object from Mask or Dsurface

Print or Summarise secr Object

Spatially Explicit Capture--Recapture

Construct Detection Model Design Matrices and Lookups

Population Size

pointsInPolygon

Points Inside Polygon

Mixture Model Check

Outline Around Mask Cells

Combine traps Objects

Plot traps Object

Print Detectors

Read Habitat Mask From File

Goodness-of-fit Test Results

Area of Polygon(s)

Print Detections

predictDsurface

Predict Density Surface

Import Telemetry Fixes

Simulate From Fitted secr Model

Combine capthist Objects

Skink Pitfall Data

Subset popn Object

transformations

Transform Point Array

Subset, Split or Combine Mask Objects

Complex Detector Layouts

Write Data to Text File

Read Detector Data From File

Random Number Seed

SECR Models Fitted to Demonstration Data

Population Object

Goodness-of-Fit Test

secr.make.newdata

Create Default Design Data

Combine popn Objects

rectangularMask

Rectangular Mask

shareFactorLevels

Fix Inconsistent Covariates

Sighting Attributes

Reformat Signal Data

Colour Strip Legend

Simulate Detection Histories

subset.capthist

Subset or Split capthist Object

Subset traps Object

Simulate 2-D Population

Detector or Mask Spacing

Sort Rows of capthist or mask Object

Detector Attributes

Non-Euclidean Distances

Summarise Habitat Mask

summary.capthist

Summarise Detections

Combine Columns

Score Test for SECR Models

Spatially Explicit Capture--Recapture Models

Utility Functions

Variance - Covariance Matrix of SECR Parameters

Slice Transect Into Shorter Sections

Smooth Terms in SECR Models

Check SECR Data

Mask Buffer Width

Summarise Detector Array

Time-varying Covariates

Plot usage, detections or sightings.

Drop Unwanted List Components

Troubleshooting

Problems in Fitting SECR Models

Specifying a Dynamic Population

Update Old capthist Format