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secr (version 4.4.8)

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

4.4.8

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

November 9th, 2021

Functions in secr (4.4.8)

Convert Data To Or From BUGS Format

Likelihood Ratio Test

Model Compatibility

Coefficient of Variation

Construct Density Design Data

Import or export data

Compare SECR Models

Frequently Asked Questions, And Others

Plot Likelihood Surface

Density Surfaces

Combine Telemetry and Detection Data

Telemetry Fixes in Polygons

Orongorongo Valley Brushtail Possums

Multi-core Processing

Convert Data to RMark Input Format

Coerce capthist to Data Frame

Initial Parameter Values for SECR

Coerce traps object to mask

RSE from Fitted Model

Smoothed Resource Surface

Closed population estimates

Coefficients of secr Object

Dissect Spatial Capture History Object

Detection Functions

Mark-resight Data

Detector Clustering

Circular Probability

Add Covariates to Mask or Traps

Spatial Capture History Object

Profile Likelihood Confidence Intervals

Contour Detection Probability

Confidence Ellipses

Distance To Nearest Detector

Derived Parameters of Fitted SECR Model

Detail Specification for secr.fit

Mask Buffer Diagnostic Plot (internal)

Expected Number of Individuals

Deviance of fitted secr model and residual degrees of freedom

Rasterize Area Search or Transect Data

House mouse live trapping data

Covariates Attribute

Mask Buffer Diagnostic Plot

Empirical Variance of H-T Density Estimate

Simulated Movements

deleteMaskPoints

Edit Mask Points

Deermouse Live-trapping Datasets

Activity Centres of Detected and Undetected Animals

First or Last Part of an Object

Home Range Statistics

Construct capthist Object

Multinomial Coefficient of SECR Likelihood

Probability Density of Home Range Centre

Hybrid Mixture Model

Logit Transformation

Combine or Split Sessions of capthist Object

Spatially Explicit Capture--Recapture by Inverse Prediction

make.systematic

Construct Systematic Detector Design

Construct Lacework Detector Design

Flat-tailed Horned Lizard Dataset

Build Detector Array on Triangular or Hexagonal Grid

Work with Open Population data

Build Habitat Mask

Mask Diagnostics

Multi-session Objects

Averaging of SECR Models Using Akaike's Information Criterion

Fit Multiple SECR Models

Ovenbird Acoustic Dataset

Net Detection Probability

Plot Detection Histories

Plot Population Object

Plot Habitat Mask, Density or Resource Surface

Key to Petal Plot

Ovenbird Mist-netting Dataset

Area of Polygon(s)

pointsInPolygon

Points Inside Polygon

Population Object

Brushtail Possum Trapping Dataset

Mixture Model Check

Outline Around Mask Cells

Plot traps Object

Print Detections

Plot Detection Functions

Print or Summarise secr Object

Build Detector Array

predictDsurface

Predict Density Surface

Read Habitat Mask From File

SECR Model Predictions

Import Telemetry Fixes

Create a RasterLayer Object from Mask or Dsurface

Print Detectors

Read Detector Data From File

Combine traps Objects

Combine popn Objects

rectangularMask

Rectangular Mask

Random Landscape

Combine capthist Objects

Construct Detection Model Design Matrices and Lookups

Spatially Explicit Capture--Recapture Models

Spatially Explicit Capture--Recapture

Create Default Design Data

secr-deprecated

Deprecated Functions in Package secr

Defunct Functions in Package secr

Combine Columns

reduce.capthist

Combine Occasions Or Detectors

Reformat Signal Data

Number of Threads

Goodness-of-fit Test Results

SECR Models Fitted to Demonstration Data

Population Size

Score Test for SECR Models

Random Number Seed

Goodness-of-Fit Test

Simulate 2-D Population

shareFactorLevels

Fix Inconsistent Covariates

Simulate Detection Histories

Sighting Attributes

Simulate From Fitted secr Model

Smooth Terms in SECR Models

Skink Pitfall Data

Slice Transect Into Shorter Sections

Sort Rows of capthist or mask Object

Detector or Mask Spacing

Summarise Detector Array

Summarise Simulated Population

Subset traps Object

Mask Buffer Width

Subset, Split or Combine Mask Objects

Subset popn Object

summary.capthist

Summarise Detections

Summarise Habitat Mask

Colour Strip Legend

subset.capthist

Subset or Split capthist Object

Update Old capthist Format

Drop Unwanted List Components

Detector Attributes

Utility Functions

Non-Euclidean Distances

Plot usage, detections or sightings.

Variance - Covariance Matrix of SECR Parameters

Complex Detector Layouts

Time-varying Covariates

transformations

Transform Point Array

Write Data to Text File

Check SECR Data

Troubleshooting

Problems in Fitting SECR Models

Specifying a Dynamic Population