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secr (version 2.0.0)

Spatially explicit capture-recapture

Description

Functions to estimate the density 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

2.0.0

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

February 21st, 2011

Functions in secr (2.0.0)

Confidence ellipse

Compare SECR Models

Build Habitat Mask

Plot Habitat Mask

Deermouse Live-trapping Datasets

Print secr Object

Covariates Attribute

Convert Data To Or From BUGS Format

Deviance of fitted secr model and residual degrees of freedom

Coefficients of secr Object

Likelihood Ratio Test for SECR Models

Spatial Capture History Object

Closed population estimates

Write Data to Text File

Read Detector Data From File

Simulate 2-D Population

subset.capthist

Subset or Split capthist Object

SECR Models Fitted to Demonstration Data

Summarise Detector Array

Model averaging for SECR Models

Ovenbird Mist-netting Dataset

Score Test for SECR Models

Probability Density of Home Range Centre

Print Detections

Skink Pitfall Data

Net Detection Probability

Detector or Mask Spacing

Population Object

Simulate Detection Histories

Spatially Explicit Capture--Recapture

Summarise Habitat Mask

Home Range Statistics

Construct capthist Object

secr.make.newdata

Create Default Design Data

Print Detectors

Check SECR Data

Sort Rows of capthist Object

Spatially Explicit Capture--Recapture Models

Dissect Spatial Capture History Object

Combine traps Objects

Frequently Asked Questions, And Others

Initial Parameter Values for SECR

Import or export data

Build Detector Array on Triangular or Hexagonal Grid

Plot Detection Histories

Exchange data with SPACECAP package

Logit Transformation

Contour Detection Probability

Construct Detection Model Design Matrices and Lookups

Build Detector Array

Read Habitat Mask From File

Ovenbird Acoustic Dataset

Simulate From Fitted secr Model

Spatially Explicit Capture--Recapture Models

Combine Columns

Subset traps Object

Plot popn Object

Brushtail Possum Trapping Dataset

Combine capthist Objects

Mask Buffer Width

Variance - Covariance Matrix of SECR Parameters

Detector Attributes

Multi-session Objects

Drop Unwanted List Components

summary.capthist

Summarise Detections

House mouse live trapping data

Mask Buffer Diagnostic Plot

Plot Detection Functions

secr.model.density

transformations

Transform Point Array

Construct Density Design Data

Detection Functions

Design-based Variance of Density

Spatially Explicit Capture--Recapture by Inverse Prediction

Mask Diagnostics

Area of simple polygon

Subset Mask Object

SECR Model Predictions

Plot likelihood surface

Profile Likelihood Confidence Intervals

Derived Parameters of Fitted SECR Model

Distance To Nearest Detector

Mask Buffer Diagnostic Plot (internal)

Multinomial Coefficient of SECR Likelihood

Plot traps Object

Combine popn Objects

reduce.capthist

Combine Occasions Or Convert Detector Types

Flat-tailed Horned Lizard Dataset

secr.model.detection

Models for Detection Parameters