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secr (version 2.10.2)

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

1,565

Version

2.10.2

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

January 9th, 2016

Functions in secr (2.10.2)

Score Test for SECR Models

Build Detector Array on Triangular or Hexagonal Grid

Detail Specification for secr.fit

Density Surfaces

Coefficient of Variation

Compare SECR Models

Plot likelihood surface

Confidence Ellipses

Construct Density Design Data

Plot popn Object

deleteMaskPoints

Edit Mask Points

First or Last Part of an Object

Telemetry Fixes in Polygons

Convert Data To Or From BUGS Format

House mouse live trapping data

Expected Number of Individuals

Activity Centres of Detected and Undetected Animals

Mark-resight Data

Multinomial Coefficient of SECR Likelihood

predictDsurface

Predict Density Surface

Orongorongo Valley Brushtail Possums

Random Landscape

Smoothed Resource Surface

Add Covariates to Mask or Traps

Ovenbird Acoustic Dataset

Spatially Explicit Capture--Recapture by Inverse Prediction

SECR Models Fitted to Demonstration Data

Multi-core Processing

Flat-tailed Horned Lizard Dataset

Mask Buffer Diagnostic Plot (internal)

Coefficients of secr Object

Detection Functions

secr.model.detection

Models for Detection Parameters

Construct capthist Object

Contour Detection Probability

Profile Likelihood Confidence Intervals

rectangularMask

Rectangular Mask

Create a RasterLayer Object from Mask or Dsurface

make.systematic

Construct Systematic Detector Design

secr.model.density

Combine Columns

Likelihood Ratio Test

Goodness-of-fit Test Results

Combine traps Objects

Logit Transformation

Dissect Spatial Capture History Object

Multi-session Objects

Simulate 2-D Population

Import Radio Fixes

Probability Density of Home Range Centre

summary.capthist

Summarise Detections

Print Detectors

Initial Parameter Values for SECR

Deermouse Live-trapping Datasets

Mask Buffer Diagnostic Plot

Combine capthist Objects

Rasterize Area Search or Transect Data

Plot Detection Histories

Simulate Detection Histories

sim.popn details

Specifying a Dynamic Population

Population Object

Subset popn Object

Read Habitat Mask From File

Ovenbird Mist-netting Dataset

Time-varying Detector Covariates

Spatially Explicit Capture--Recapture

Sighting Attributes

Summarise Detector Array

subset.capthist

Subset or Split capthist Object

Combine popn Objects

Colour Strip Legend

Utility Functions

Exchange data with SPACECAP package

Empirical Variance of H-T Density Estimate

transformations

Transform Point Array

Detector Attributes

pointsInPolygon

Points Inside Polygon

Circular Probability

Check SECR Data

Troubleshooting

Problems in Fitting SECR Models

Subset traps Object

Smooth Terms in SECR Models

Convert Data to RMark Input Format

Goodness-of-Fit Test

reduce.capthist

Combine Occasions Or Detectors

Complex Detector Layouts

secr.make.newdata

Create Default Design Data

Sort Rows of capthist or mask Object

Combine Telemetry and Detection Data

Spatially Explicit Capture--Recapture Models

Detector or Mask Spacing

Distance To Nearest Detector

Hybrid Mixture Model

Build Detector Array

Mask Diagnostics

Print Detections

Subset Mask Object

Non-Euclidean Distances

Spatial Capture History Object

Combine or Split Sessions of capthist Object

Averaging of SECR Models Using Akaike's Information Criterion

Fit Multiple SECR Models

Mixture Model Check

SECR Model Predictions

Area of Polygon(s)

Print secr Object

Skink Pitfall Data

Slice Transect Into Shorter Sections

Import or export data

Drop Unwanted List Components

Variance - Covariance Matrix of SECR Parameters

Closed population estimates

Covariates Attribute

Derived Parameters of Fitted SECR Model

Plot Habitat Mask, Density or Resource Surface

Brushtail Possum Trapping Dataset

Read Detector Data From File

Population Size

Simulate From Fitted secr Model

Mask Buffer Width

Detector Clustering

Deviance of fitted secr model and residual degrees of freedom

Frequently Asked Questions, And Others

Build Habitat Mask

Net Detection Probability

Plot traps Object

Plot Detection Functions

Reformat Signal Data

Spatially Explicit Capture--Recapture Models

Home Range Statistics

Construct Detection Model Design Matrices and Lookups

Summarise Habitat Mask

Write Data to Text File