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secr (version 2.3.2)

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

2.3.2

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

May 15th, 2012

Functions in secr (2.3.2)

Logit Transformation

Spatially Explicit Capture--Recapture

secr.make.newdata

Create Default Design Data

Add Covariates to Mask or Traps

Detector Attributes

subset.capthist

Subset or Split capthist Object

Import or export data

Deermouse Live-trapping Datasets

Frequently Asked Questions, And Others

Confidence ellipse

Construct Density Design Data

Mask Diagnostics

Combine or Split Sessions of capthist Object

Convert Data To Or From BUGS Format

make.systematic

Construct Systematic Detector Design

Plot Detection Histories

Ovenbird Acoustic Dataset

Model averaging for SECR Models

Construct Detection Model Design Matrices and Lookups

rectangularMask

Rectangular Mask

Plot Detection Functions

Print Detectors

Population Size

Brushtail Possum Trapping Dataset

Build Habitat Mask

Combine capthist Objects

Skink Pitfall Data

Combine traps Objects

Area of Polygon(s)

Dissect Spatial Capture History Object

secr.model.detection

Models for Detection Parameters

Build Detector Array on Triangular or Hexagonal Grid

House mouse live trapping data

Score Test for SECR Models

predictDsurface

Predict Density Surface

Simulate Detection Histories

Summarise Detector Array

Construct capthist Object

Read Habitat Mask From File

Sort Rows of capthist Object

Detector or Mask Spacing

troubleshooting

Problems in Fitting SECR Models

Likelihood Ratio Test

Combine popn Objects

Deviance of fitted secr model and residual degrees of freedom

SECR Models Fitted to Demonstration Data

Circular Probability

secr.model.density

Write Data to Text File

Simulate From Fitted secr Model

Initial Parameter Values for SECR

summary.capthist

Summarise Detections

Detector Clustering

Drop Unwanted List Components

Print Detections

Probability Density of Home Range Centre

transformations

Transform Point Array

Closed population estimates

Read Detector Data From File

Mask Buffer Diagnostic Plot (internal)

Spatially Explicit Capture--Recapture Models

Expected Number of Individuals

Multinomial Coefficient of SECR Likelihood

Coefficients of secr Object

Distance To Nearest Detector

Contour Detection Probability

Ovenbird Mist-netting Dataset

Population Object

Plot popn Object

Compare SECR Models

Spatial Capture History Object

pointsInPolygon

Points Inside Polygon

Mask Buffer Width

Convert Data to RMark Input Format

Covariates Attribute

Combine Columns

Mask Buffer Diagnostic Plot

Check SECR Data

Subset Mask Object

Subset popn Object

Spatially Explicit Capture--Recapture by Inverse Prediction

Net Detection Probability

Subset traps Object

Simulate 2-D Population

Derived Parameters of Fitted SECR Model

Profile Likelihood Confidence Intervals

Detection Functions

Empirical Variance of H-T Density Estimate

Home Range Statistics

First or Last Part of an Object

Density Surfaces

Plot traps Object

Print secr Object

Spatially Explicit Capture--Recapture Models

Complex Detector Layouts

Plot likelihood surface

Exchange data with SPACECAP package

Flat-tailed Horned Lizard Dataset

Build Detector Array

Multi-session Objects

Plot Habitat Mask or Density Surface

SECR Model Predictions

reduce.capthist

Combine Occasions Or Convert Detector Types

Random Landscape

Summarise Habitat Mask

Variance - Covariance Matrix of SECR Parameters