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secr (version 3.1.6)

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

1,407

Version

3.1.6

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

May 14th, 2018

Functions in secr (3.1.6)

Import or export data

Plot Likelihood Surface

Deviance of fitted secr model and residual degrees of freedom

Rasterize Area Search or Transect Data

Compare SECR Models

Coerce capthist to Data Frame

Distance To Nearest Detector

Coerce traps object to mask

Multinomial Coefficient of SECR Likelihood

Likelihood Ratio Test

Coefficient of Variation

Closed population estimates

Construct capthist Object

Multi-session Objects

Detail Specification for secr.fit

Plot traps Object

Key to Petal Plot

Orongorongo Valley Brushtail Possums

Telemetry Fixes in Polygons

Exchange data with SPACECAP package

Construct Density Design Data

Multi-core Processing

Mask Buffer Diagnostic Plot

Mask Buffer Diagnostic Plot (internal)

Detection Functions

Outline Around Mask Cells

make.systematic

Construct Systematic Detector Design

Random Landscape

Coefficients of secr Object

Build Habitat Mask

Build Detector Array

Convert Data To Or From BUGS Format

Plot popn Object

Plot Detection Functions

Build Detector Array on Triangular or Hexagonal Grid

Convert Data to RMark Input Format

deleteMaskPoints

Edit Mask Points

Profile Likelihood Confidence Intervals

Derived Parameters of Fitted SECR Model

Create a RasterLayer Object from Mask or Dsurface

Probability Density of Home Range Centre

Import Telemetry Fixes

Area of Polygon(s)

Add Covariates to Mask or Traps

Smoothed Resource Surface

Detector Clustering

Initial Parameter Values for SECR

Read Detector Data From File

Population Object

Construct Detection Model Design Matrices and Lookups

Hybrid Mixture Model

Reformat Signal Data

Spatially Explicit Capture--Recapture

Contour Detection Probability

rectangularMask

Rectangular Mask

Subset Mask Object

House mouse live trapping data

Subset popn Object

Spatial Capture History Object

Confidence Ellipses

Combine Columns

Goodness-of-fit Test Results

Deermouse Live-trapping Datasets

Combine or Split Sessions of capthist Object

Covariates Attribute

First or Last Part of an Object

Empirical Variance of H-T Density Estimate

Logit Transformation

Ovenbird Mist-netting Dataset

Home Range Statistics

Ovenbird Acoustic Dataset

Fit Multiple SECR Models

Simulate 2-D Population

Simulate Detection Histories

Mask Diagnostics

Sort Rows of capthist or mask Object

Net Detection Probability

Detector or Mask Spacing

Expected Number of Individuals

Brushtail Possum Trapping Dataset

Activity Centres of Detected and Undetected Animals

Detector Attributes

Summarise Habitat Mask

summary.capthist

Summarise Detections

Averaging of SECR Models Using Akaike's Information Criterion

Spatially Explicit Capture--Recapture by Inverse Prediction

SECR Model Predictions

Flat-tailed Horned Lizard Dataset

Non-Euclidean Distances

Combine traps Objects

Specifying a Dynamic Population

Mixture Model Check

Work with Open Population data

Read Habitat Mask From File

Utility Functions

Update Old capthist Format

pointsInPolygon

Points Inside Polygon

Plot Detection Histories

Combine capthist Objects

Print secr Object

secr.make.newdata

Create Default Design Data

Print Detectors

Plot Habitat Mask, Density or Resource Surface

Combine popn Objects

Random Number Seed

Goodness-of-Fit Test

SECR Models Fitted to Demonstration Data

predictDsurface

Predict Density Surface

Simulate From Fitted secr Model

Skink Pitfall Data

Subset traps Object

Smooth Terms in SECR Models

Print Detections

Slice Transect Into Shorter Sections

Drop Unwanted List Components

Mask Buffer Width

Troubleshooting

Problems in Fitting SECR Models

reduce.capthist

Combine Occasions Or Detectors

Write Data to Text File

Population Size

Score Test for SECR Models

shareFactorLevels

Fix Inconsistent Covariates

Spatially Explicit Capture--Recapture Models

Summarise Detector Array

Sighting Attributes

Colour Strip Legend

Time-varying Covariates

Variance - Covariance Matrix of SECR Parameters

subset.capthist

Subset or Split capthist Object

Check SECR Data

transformations

Transform Point Array

Complex Detector Layouts

Plot usage, detections or sightings.

Frequently Asked Questions, And Others

Density Surfaces

Mark-resight Data

Combine Telemetry and Detection Data

Dissect Spatial Capture History Object

Circular Probability