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secr (version 2.3.0)

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

1,565

Version

2.3.0

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

November 20th, 2011

Functions in secr (2.3.0)

Compare SECR Models

Convert Data To Or From BUGS Format

Dissect Spatial Capture History Object

Frequently Asked Questions, And Others

Add Covariates to Mask or Traps

Exchange data with SPACECAP package

Circular Probability

Closed population estimates

Initial Parameter Values for SECR

SECR Models Fitted to Demonstration Data

Mask Buffer Diagnostic Plot (internal)

Logit Transformation

Probability Density of Home Range Centre

Mask Buffer Diagnostic Plot

Density Surfaces

Deviance of fitted secr model and residual degrees of freedom

Detection Functions

predictDsurface

Predict Density Surface

Contour Detection Probability

Ovenbird Acoustic Dataset

Combine popn Objects

Plot traps Object

Model averaging for SECR Models

House mouse live trapping data

Detector or Mask Spacing

Flat-tailed Horned Lizard Dataset

rectangularMask

Rectangular Mask

Build Detector Array

Coefficients of secr Object

Print secr Object

Distance To Nearest Detector

Print Detectors

Plot Habitat Mask or Density Surface

Ovenbird Mist-netting Dataset

Plot popn Object

Plot Detection Functions

Print Detections

secr.make.newdata

Create Default Design Data

Simulate From Fitted secr Model

Build Habitat Mask

Home Range Statistics

Likelihood Ratio Test for SECR Models

Build Detector Array on Triangular or Hexagonal Grid

Plot likelihood surface

Net Detection Probability

Subset popn Object

Brushtail Possum Trapping Dataset

pointsInPolygon

Points Inside Polygon

Deermouse Live-trapping Datasets

Population Object

Spatial Capture History Object

First or Last Part of an Object

Spatially Explicit Capture--Recapture Models

Combine Columns

Plot Detection Histories

Empirical Variance of H-T Density Estimate

Combine capthist Objects

Spatially Explicit Capture--Recapture by Inverse Prediction

Construct capthist Object

make.systematic

Construct Systematic Detector Design

SECR Model Predictions

Simulate Detection Histories

Combine traps Objects

Simulate 2-D Population

Variance - Covariance Matrix of SECR Parameters

Spatially Explicit Capture--Recapture

Summarise Detector Array

Drop Unwanted List Components

Score Test for SECR Models

subset.capthist

Subset or Split capthist Object

Skink Pitfall Data

Check SECR Data

transformations

Transform Point Array

Read Habitat Mask From File

Complex Detector Layouts

Read Detector Data From File

Subset Mask Object

summary.capthist

Summarise Detections

Sort Rows of capthist Object

troubleshooting

Problems in Fitting SECR Models

Summarise Habitat Mask

Detector Attributes

Write Data to Text File

Confidence ellipse

Covariates Attribute

Area of Polygon(s)

Expected Number of Individuals

Derived Parameters of Fitted SECR Model

Population Size

Multinomial Coefficient of SECR Likelihood

secr.model.density

reduce.capthist

Combine Occasions Or Convert Detector Types

secr.model.detection

Models for Detection Parameters

Spatially Explicit Capture--Recapture Models

Detector Clustering

Construct Detection Model Design Matrices and Lookups

Subset traps Object

Mask Buffer Width

Construct Density Design Data

Import or export data

Multi-session Objects

Profile Likelihood Confidence Intervals

Mask Diagnostics