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secr (version 3.1.5)

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

1,551

Version

3.1.5

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

February 25th, 2018

Functions in secr (3.1.5)

Frequently Asked Questions, And Others

Mark-resight Data

Add Covariates to Mask or Traps

Detail Specification for secr.fit

Initial Parameter Values for SECR

Combine Telemetry and Detection Data

Expected Number of Individuals

Covariates Attribute

Deermouse Live-trapping Datasets

Closed population estimates

Spatial Capture History Object

Detection Functions

Construct Density Design Data

Convert Data To Or From BUGS Format

Activity Centres of Detected and Undetected Animals

Home Range Statistics

Contour Detection Probability

First or Last Part of an Object

House mouse live trapping data

Telemetry Fixes in Polygons

Coerce traps object to mask

Dissect Spatial Capture History Object

Circular Probability

Multi-core Processing

Net Detection Probability

Mask Buffer Diagnostic Plot

Ovenbird Mist-netting Dataset

Ovenbird Acoustic Dataset

Fit Multiple SECR Models

Print secr Object

Detector Clustering

Deviance of fitted secr model and residual degrees of freedom

Mask Buffer Diagnostic Plot (internal)

deleteMaskPoints

Edit Mask Points

Rasterize Area Search or Transect Data

Probability Density of Home Range Centre

Import Telemetry Fixes

Print Detectors

Hybrid Mixture Model

Distance To Nearest Detector

Multinomial Coefficient of SECR Likelihood

Derived Parameters of Fitted SECR Model

Confidence Ellipses

Combine or Split Sessions of capthist Object

Construct capthist Object

Multi-session Objects

Key to Petal Plot

Empirical Variance of H-T Density Estimate

Read Detector Data From File

Logit Transformation

Plot popn Object

Flat-tailed Horned Lizard Dataset

Plot Detection Functions

Random Landscape

Random Number Seed

Build Habitat Mask

SECR Models Fitted to Demonstration Data

Build Detector Array

make.systematic

Construct Systematic Detector Design

Work with Open Population data

Build Detector Array on Triangular or Hexagonal Grid

Spatially Explicit Capture--Recapture by Inverse Prediction

Mask Diagnostics

Create a RasterLayer Object from Mask or Dsurface

Plot Detection Histories

Simulate From Fitted secr Model

Plot Habitat Mask, Density or Resource Surface

Combine traps Objects

Mixture Model Check

Plot traps Object

Averaging of SECR Models Using Akaike's Information Criterion

Read Habitat Mask From File

Outline Around Mask Cells

pointsInPolygon

Points Inside Polygon

Print Detections

predictDsurface

Predict Density Surface

Skink Pitfall Data

secr.make.newdata

Create Default Design Data

Goodness-of-Fit Test

Sort Rows of capthist or mask Object

Smooth Terms in SECR Models

reduce.capthist

Combine Occasions Or Detectors

Area of Polygon(s)

Detector or Mask Spacing

Population Size

Construct Detection Model Design Matrices and Lookups

Population Object

Brushtail Possum Trapping Dataset

rectangularMask

Rectangular Mask

Combine Columns

Slice Transect Into Shorter Sections

Spatially Explicit Capture--Recapture

Simulate Detection Histories

Simulate 2-D Population

SECR Model Predictions

subset.capthist

Subset or Split capthist Object

transformations

Transform Point Array

Colour Strip Legend

Subset traps Object

Combine capthist Objects

Mask Buffer Width

Combine popn Objects

Goodness-of-fit Test Results

Reformat Signal Data

Score Test for SECR Models

Spatially Explicit Capture--Recapture Models

Complex Detector Layouts

summary.capthist

Summarise Detections

Drop Unwanted List Components

Troubleshooting

Problems in Fitting SECR Models

Write Data to Text File

Summarise Habitat Mask

Plot usage, detections or sightings.

Specifying a Dynamic Population

Update Old capthist Format

Subset Mask Object

shareFactorLevels

Fix Inconsistent Covariates

Sighting Attributes

Subset popn Object

Detector Attributes

Variance - Covariance Matrix of SECR Parameters

Check SECR Data

Summarise Detector Array

Time-varying Detector Covariates

Non-Euclidean Distances

Utility Functions

Likelihood Ratio Test

Orongorongo Valley Brushtail Possums

Convert Data to RMark Input Format

Coefficients of secr Object

Smoothed Resource Surface

Compare SECR Models

Profile Likelihood Confidence Intervals

Density Surfaces

Coefficient of Variation

Exchange data with SPACECAP package

Import or export data

Coerce capthist to Data Frame

Plot Likelihood Surface