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secr (version 1.5.1)

Spatially explicit capture-recapture

Description

Estimate animal population density with capture-recapture data from an array of passive detectors (traps). 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

1.5.1

License

GPL (>= 2)

Maintainer

Murray Efford

Last Published

December 3rd, 2010

Functions in secr (1.5.1)

Profile Likelihood Confidence Intervals

Combine popn Objects

Brushtail Possum Trapping Dataset

Read Detector Data From File

Ovenbird Mist-netting Dataset

summary.capthist

Summarise Detections

Detector Attributes

Contour Detection Probability

Construct Density Design Data

Exchange data with SPACECAP package

Deviance of fitted secr model and residual degrees of freedom

Print secr Object

Design-based Variance of Density

Distance To Nearest Detector

Build Detector Array on Triangular or Hexagonal Grid

Mask Buffer Diagnostic Plot

Plot Detection Functions

Population Object

Print Detectors

Spatially Explicit Capture--Recapture

SECR Models Fitted to Demonstration Data

secr.model.density

Mask Buffer Width

Drop Unwanted List Components

Check SECR Data

Likelihood Ratio Test for SECR Models

Closed population estimates

Frequently Asked Questions, And Others

Net Detection Probability

Spatial Capture History Object

Model averaging for SECR Models

Plot Detection Histories

Plot likelihood surface

Area of simple polygon

Subset Mask Object

House mouse live trapping data

Print Detections

Detection Functions

Ovenbird Acoustic Dataset

Simulate 2-D Population

Mask Buffer Diagnostic Plot (internal)

Build Detector Array

Construct Detection Model Design Matrices and Lookups

Mask Diagnostics

Dissect Spatial Capture History Object

Read Habitat Mask From File

Import or export data

secr.make.newdata

Create Default Design Data

Multinomial Coefficient of SECR Likelihood

Combine traps Objects

Simulate Detection Histories

Simulate From Fitted secr Model

subset.capthist

Subset or Split capthist Object

Detector or Mask Spacing

Combine Columns

Plot popn Object

Confidence ellipse

Spatially Explicit Capture--Recapture Models

Spatially Explicit Capture--Recapture by Inverse Prediction

Home Range Statistics

Derived Parameters of Fitted SECR Model

SECR Model Predictions

Summarise Detector Array

Coefficients of secr Object

Variance - Covariance Matrix of SECR Parameters

Write Data to Text File

Compare SECR Models

Covariates Attribute

Multi-session Objects

reduce.capthist

Combine Occasions

Logit Transformation

Plot Habitat Mask

Initial Parameter Values for SECR

Spatially Explicit Capture--Recapture Models

Skink Pitfall Data

Deermouse Live-trapping Datasets

Combine capthist Objects

Construct capthist Object

secr.model.detection

Models for Detection Parameters

transformations

Transform Point Array

Plot traps Object

Score Test for SECR Models

Subset traps Object

Summarise Habitat Mask

Build Habitat Mask