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secr (version 4.3.0)

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

1,470

Version

4.3.0

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

July 14th, 2020

Functions in secr (4.3.0)

Likelihood Ratio Test

Density Surfaces

Frequently Asked Questions, And Others

Import or export data

Convert Data To Or From BUGS Format

Construct Density Design Data

Plot Likelihood Surface

Coefficient of Variation

Compare SECR Models

Model Compatibility

RSE from Fitted Model

Add Covariates to Mask or Traps

Smoothed Resource Surface

Mark-resight Data

Circular Probability

Coefficients of secr Object

Detector Clustering

Multi-core Processing

Coerce traps object to mask

Orongorongo Valley Brushtail Possums

Initial Parameter Values for SECR

Convert Data to RMark Input Format

Deermouse Live-trapping Datasets

House mouse live trapping data

Covariates Attribute

Probability Density of Home Range Centre

Activity Centres of Detected and Undetected Animals

Telemetry Fixes in Polygons

Closed population estimates

Home Range Statistics

Profile Likelihood Confidence Intervals

Confidence Ellipses

Contour Detection Probability

Detection Functions

Distance To Nearest Detector

Averaging of SECR Models Using Akaike's Information Criterion

Combine Telemetry and Detection Data

Combine or Split Sessions of capthist Object

Mask Diagnostics

Plot Habitat Mask, Density or Resource Surface

Area of Polygon(s)

Plot Detection Histories

Spatially Explicit Capture--Recapture by Inverse Prediction

Population Object

Build Habitat Mask

Deviance of fitted secr model and residual degrees of freedom

Work with Open Population data

Random Landscape

Flat-tailed Horned Lizard Dataset

Logit Transformation

deleteMaskPoints

Edit Mask Points

Expected Number of Individuals

Mask Buffer Diagnostic Plot (internal)

Plot Population Object

Create a RasterLayer Object from Mask or Dsurface

Construct Detection Model Design Matrices and Lookups

make.systematic

Construct Systematic Detector Design

Ovenbird Mist-netting Dataset

Ovenbird Acoustic Dataset

Hybrid Mixture Model

SECR Model Predictions

Rasterize Area Search or Transect Data

Spatially Explicit Capture--Recapture

Build Detector Array

Brushtail Possum Trapping Dataset

Plot Detection Functions

First or Last Part of an Object

Multinomial Coefficient of SECR Likelihood

Key to Petal Plot

Multi-session Objects

Build Detector Array on Triangular or Hexagonal Grid

Mixture Model Check

pointsInPolygon

Points Inside Polygon

predictDsurface

Predict Density Surface

Net Detection Probability

Print Detections

Population Size

Fit Multiple SECR Models

rectangularMask

Rectangular Mask

Reformat Signal Data

Simulate Detection Histories

Coerce capthist to Data Frame

reduce.capthist

Combine Occasions Or Detectors

Combine Columns

Subset, Split or Combine Mask Objects

subset.capthist

Subset or Split capthist Object

Drop Unwanted List Components

Summarise Detector Array

Time-varying Covariates

Troubleshooting

Problems in Fitting SECR Models

Skink Pitfall Data

Print or Summarise secr Object

Spatial Capture History Object

Combine capthist Objects

Score Test for SECR Models

Import Telemetry Fixes

Print Detectors

Read Detector Data From File

Combine popn Objects

Random Number Seed

Simulate 2-D Population

Smooth Terms in SECR Models

Simulate From Fitted secr Model

Number of Threads

SECR Models Fitted to Demonstration Data

Spatially Explicit Capture--Recapture Models

Sighting Attributes

Dissect Spatial Capture History Object

Update Old capthist Format

Summarise Habitat Mask

Specifying a Dynamic Population

Colour Strip Legend

Non-Euclidean Distances

Summarise Simulated Population

Slice Transect Into Shorter Sections

Derived Parameters of Fitted SECR Model

Mask Buffer Width

shareFactorLevels

Fix Inconsistent Covariates

Sort Rows of capthist or mask Object

summary.capthist

Summarise Detections

Construct capthist Object

Empirical Variance of H-T Density Estimate

Detail Specification for secr.fit

Construct Lacework Detector Design

Mask Buffer Diagnostic Plot

Utility Functions

Subset traps Object

Write Data to Text File

Detector Attributes

Variance - Covariance Matrix of SECR Parameters

Subset popn Object

Outline Around Mask Cells

Plot traps Object

Combine traps Objects

Read Habitat Mask From File

secr.make.newdata

Create Default Design Data

Check SECR Data

Goodness-of-fit Test Results

Goodness-of-Fit Test

Detector or Mask Spacing

Complex Detector Layouts

transformations

Transform Point Array

Plot usage, detections or sightings.